• Journal of the Korean Statistical Society
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• 제25권1호
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• pp.1-24
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• 1996

In selecting a final tree, Breiman, Friedman, Olshen, and Stone(1984) compare the prediction risks of a pair of tree, where one contains the other, using the standard error of the prediction risk of the larger one. This paper proposes an approach to selection of a final tree by using the standard error of the difference of the prediction risks between a pair of trees rather than the standard error of the larger one. This approach is compared with CART's for simulated data from a simple regression model. Asymptotic results of the approaches are also derived and compared to each other. Both the asymptotic and the simulation results indicate that final trees by CART tend to be smaller than desired.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1990년도 춘계공동학술대회논문집; 한국과학기술원; 28 Apr. 1990
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• pp.254-262
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• 1990

A predictive functional relationship model is presented for the calibration problem in which the standard as well as the nonstandard measurements are subject to error. For the estimation of the relationship between the two measurements, the ordinary least squares and maximum likelihood estimation methods are considered, while for the prediction of unknown standard measurementswe consider direct and inverse approaches. Relative performances of those calibration procedures are compared in terms of the asymptotic mean square error of prediction.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 춘계학술대회
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• pp.19-24
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• 2004

A number of creep data were collected and filed for type 316LN stainless steels through literature survey and experimental data produced in KAERI. Using these data, polynomial equations for predicting creep life were obtained for Larson Miller (L-M), Qrr-Sherby-Dorn (O-S-D) and Manson-Haferd (M-H) parametric methods. In order to find out the suitability for them, the relative standard error (RSE) and standard error of estimate (SEE) values were obtained by statistical process of creep data. The O-S-D parameter showed better fitting to creep-rupture data than the L-M or the M-H parameters, and the three parametric methods did not generate the large difference in the SEE and the RSE values.

• 환경위생공학
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• 제23권2호
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• pp.19-25
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• 2008

For measurement of tylosin, ammonia nitrogen, and glucose concentration during the culture of Streptomyces fradiae using Near Infrared Spectroscopy, the calibration using various mathematical models was performed and then, based on the linear model, the validation was carried out. In the case of sucrose concentration using the MLR method, the Standard Error of Prediction and Multiple correlation coefficient were 1.97, and 0.991, respectively. In the case of ammonia nitrogen concentration using the PLSR method, the Standard Error of Prediction and Multiple correlation coefficient were 0.13, and 0.990, respectively. In the case of tylosin concentration using the PLSR method, the standard Error of Prediction and Multiple correlation coefficient were 0.54, and 0.984, respectively.

• 대한산업공학회지
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• 제17권2호
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• pp.97-105
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• 1991

In developing a regression relationship for a standard data system in work measurement, job characteristics are frequently measured with error when measurements are made in the field under less controlled conditions or when accurate instruments are not available. This paper concerns with the prediction of the total task time when job characteristics are measured with error. Integrated mean square error of prediction(IMSE) is developed as a measure of the effect of errors in job characteristics on the predicted total task time. By evaluating how IMSE is affected by the measurement error in each job characteristic, we can determine which error should be controlled to develop a desirable standard data system.

• Journal of the Korean Data and Information Science Society
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• 제21권4호
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• pp.803-811
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• 2010

This study analyzes the characteristics of preference ratings by dividing estimated values into four groups according to rank correlation coefficient after obtaining preference estimated value to user's ratings by using collaborative filtering algorithm. It is known that the value of standard error of skewness and standard error of kurtosis lower in the group of higher rank correlation coefficient This explains that the preference of higher rank correlation coefficient has lower extreme values and the differences of preference rating values. In addition, top n recommendation lists are made after obtaining rank fitting by using the result ranks of prediction value and the ranks of real rated values, and this top n is applied to the four groups. The value of top n recommendation is calculated higher in the group of higher rank correlation coefficient, and the recommendation accuracy in the group of higher rank correlation coefficient is higher than that in the group of lower rank correlation coefficient Thus, when using standard error of skewness and standard error of kurtosis in recommender system, rank correlation coefficient can be higher, and so the accuracy of recommendation prediction can be increased.

• 한국산업융합학회 논문집
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• 제5권2호
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• pp.103-110
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• 2002

An artificial neural network is applied to the prediction of compressive strength, slump value of concrete. Standard mixed tables arc trained and estimated, and the results are compared with those of experiments. To consider the varieties of material properties, the standard mixed tables of two companies of Ready Mixed Concrete are used. And they are trained with the neural network. In this paper, standard back propagation network is used. For the arrangement on the approval of prediction of compressive strength and slump value, the standard compressive strength of 210, $240kgf/cm^2$ and target slump value of 12, 15cm are used because the amount of production of that range arc the most at ordinary companies. In results, in the prediction of compressive strength and slump value, the predicted values are converged well to those of standard mixed tables at the target error of 0.10, 0.05, 0.001 regardless of two companies.

• 약학회지
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• 제47권5호
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• pp.261-265
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• 2003

Near-infrared (NIR) system was used to determine rapidly and simply indomethacin in buffer solution for a dissolution test of tablets and capsules. Indomethacin standards were prepared ranging from 10 to 50 ppm using the mixture of phosphate buffer (pH 7.2) and water (1 : 4). The near-infrared (NIR) transmittance spectra of indomethacin standard solutions were collected by using a quartz cell in 1 mm and 2 mm pathlength. Partial least square regression (PLSR) was explored to develop calibration models over the spectral range 1100∼1700 nm. The model using 1 mm quartz cell was better than that using 2 mm quartz cell. The PLSR models developed gave standard error of prediction (SEP) of 0.858 ppm. In order to validate the developed calibration model, routine analysis was performed using another standard solutions. The NIR routine analysis showed good correlation with actual values. Standard error of prediction (SEP) is 1.414 ppm for 7 indomethacin samples in routine analysis and its error was permeable in the regulation of Korean Pharmacopoeia (VII). These results show the potential use of the real time monitoring for indomethacin during a dissolution test.

• 대한화학회지
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• 제46권4호
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• pp.309-317
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• 2002

형광분광법에 의하여 주성분 회귀분석(principal component regression, PCR)과 부분 최소자승법(Partial least squares, PLS)을 이용하여 아미노산(Tryptophan and Tyrosine)을 동시에 정량하는 방법에 대하여 연구하였다. 아미노산 혼합물의 형광 스펙트럼은 들뜸파장을257nm로 고정하여 측정하였다. 두 가지 아미노산이 서로 다른 농도로 혼합되어 있는 32개의 시료용액을 280nm∼500nm 범위에서 스펙트럼들을 얻었고 이를 이용하여 PCR과 PLS회귀모델을 얻었다. 두 가지 아미노산이 서로 다른 농도로 포함된 6개의 외부검정용 시료들의 스펙트럼들을 이용해서 회귀모델의 적합성을 검정하기 위하여 외부검정용 시료의 농도를 계산하였다. 계산된 농도를 이용하여 relative standard error of prediction($RSEP_a$)를 얻었고 같은 방법으로 overall relative standard error of prediction($RSEP_m$) 도 구하였다

• 대한기계학회논문집A
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• 제31권2호
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• pp.160-165
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• 2007

To predict long-term creep life from short-term creep life data, various parametric methods such as Larson-Mille. (L-M), Orr-Sherby-Dorn (O-S-D), Manson-Haferd (M-H) parameters, and a Minimum Commitment Method (MCM) were suggested. A number of the creep data were collected through literature surveys and experimental data produced in KAERI. The polynomial equations for type 316LN SS were obtained by the time-temperature parameters (TTP) and the MCM. Standard error (SE) and standard error of mean (SEM) values were obtained and compared with the each method for various temperatures. The TTP methods showed good creep-life prediction, but the MCM was much superior to the TTP ones at $700^{\circ}C$ and $750^{\circ}C$. It was found that the MCM were lower in the SE values when compared to the TTP methods.