• 한국국방경영분석학회지
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• 제5권2호
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• pp.27-38
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• 1979

This method explores a method of aggregating the measures of effectiveness of a weapon system from its characteristics. With this method, the constant sum method and multiple regression are used to develop a functional relationship between system effectiveness and system characteristics. As an example, a study of a tank weapon system was${\cdot}$conducted with data from the U.S. Army Armor School. It was concluded that the aggregation method is feasible, and that for the tank system studied, the reciprocals of system characteristics give a good estimating equation for measuring tank system effectiveness.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2005년도 연구개발 발표회 논문집
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• pp.278-283
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• 2005

Generally Jar-Test is available to determine the coagulant dosage rate. Disadventages associated with Jar-Test are that regular samples have to be taken requiring manual intervention and the limitation to feedback control. To deal with this difficulty, determined optimized dosage rates of coagulant to investigates the union operation method of the statistical equation which uses the multi-regression method and the SCD.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2004년도 유체기계 연구개발 발표회 논문집
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• pp.275-281
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• 2004

Generally Jar-Test is available to determine the coagulant dosage rate. Disadventages associated with Jar-Test are that regular samples have to be taken requiring manual intervention and the limitation to feedback control. To deal with this difficulty, determined optimized dosage rates of coagulant to Investigates the union operation method of the statistical equation which uses the multi-regression method and the SCD.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2000년도 학술발표회 발표논문집
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• pp.412-418
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• 2000

The purpose of this study is estimation of daily runoff in the watershed with insufficient hydrological data using tank model. In order to estimate, twentysix watersheds were selected to calibrate tank model parameters that were defined by a trial and error method. Results were correlated with characteristics of watershed. Relationships between the parameters and the watershed characteristics were derived by a multiple regression analysis. The simulation results were in agreement with the observed data.

• 대한소아치과학회지
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• 제34권3호
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• pp.430-437
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• 2007

현재 혼합치열 분석 방법으로 가장 널리 사용되고 있는 Moyers의 예측표나 Tanaka와 Johnston의 예측방정식은 북유럽 인종의 백인 자료를 바탕으로 만들어졌기 때문에 한국인에게 적용하기에는 무리가 있다. 또한 최근에는 이들이 제시한 하악 전치에 기초한 방법이 미맹출 견치와 소구치 폭경의 합을 예측하기 위한 최적의 예측인자인지에 대해서도 의문이 제기되고 있다. 본 연구의 목적은 한국인 집단을 대상으로 미맹출 견치와 소구치의 근원심 폭경을 예측하기 위한 최적의 예측인자가 어떤 치아의 조합인지 밝히고, 그 조합을 이용한 예측 방정식을 제시하며, 새로운 예측 방정식의 임상 적용을 위해 그 타당성을 검증하는 것이다. 완전한 영구치열을 가진 성인 178명(남자 108명, 여자 70명, 평균 나이 21.63세)의 자료를 기초로 예측방정식을 도출하였으며, 53명의 청소년(남자 25명, 여자 28명, 평균 나이 14.22세)으로 검증집단을 구성하여 그 타당성을 검증하였다. 그 결과 다음과 같은 결론을 얻었다. 1. 한국인 혼합치열기 청소년에서 미맹출 견치와 소구치 폭경의 합을 예측하기 위한 최적의 치아 조합은 상악 중절치, 하악 측절치, 상악 제1대구치 폭경의 합이었다($r=0.65{\sim}0.80$). 2. 상악 중절치, 하악 측절치, 상악 제1대구치 폭경의 합을 기초로 하고 부가적인 설명 변수로 성별과 악궁을 포함시켜 계산한 예측 방정식은 다음과 같이 계산되었다. 남자, 상악: $Y\;=\;0.332{\times}X_0\;+\;6.195$ 남자, 하악: $Y\;=\;0.332{\times}X_0\;+\;5.269$ 여자, 상악: $Y\;=\;0.332{\times}X_0\;+\;5.929$ 여자, 하악: $Y\;=\;0.332{\times}X_0\;+\;5.003$ 예측 방정식의 설명력은 64%였으며 표준오차(SEE)는 0.71mm였다. 3. 새로운 예측 방정식을 검증 집단에 적용하여 검증한 결과, 약 97%에서 실제 측정한 견치와 소구치 폭경의 합과 예측치와의 차이가 1mm 이하였다.

• Asian-Australasian Journal of Animal Sciences
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• 제16권2호
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• pp.172-175
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• 2003

The regression equations of dry weight of planktonic biomass upon physico-chemical characteristics of fifteen ponds in three replicates under the influence of artificial feed, broiler manure, buffalo manure, N:P:K (25:25:0) and a control pond was obtained after one year of experimental period by using stepwise regression method. Water samples from each of the ponds were analyzed daily. However, the average values were calculated on the basis of 15 day intervals designated as fortnight. In artificial feed supplemented pond the regression of average nitrates on dry weight of planktonic biomass accounted for 71.7% of the variation in biomass. In broiler manure fertilization pond the regression of total nitrogen on dry weight of planktonic biomass held it responsible for more than 74.6% of variation in biomass. In buffalo's manure fertilized pond more than 82% of the variations in biomass were due to total nitrogen. In case of N:P:K (25:25:0) treated pond 66% of the variation in the dry weight of planktonic biomass was due to average nitrates. The control pond showed the dependence of biomass on light penetration. This equation explained more than 62 percent of variation in biomass. Other variables also showed some contribution towards variation in biomass under all the treatments in these regression studies.

• 품질경영학회지
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• 제47권4호
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• pp.687-700
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• 2019

Purpose: The purpose of this study is to investigate the interaction effects between price determinants of artworks. We expand the methodology in art market by applying machine learning techniques to estimate the price of artworks and compare linear regression and machine learning in terms of prediction accuracy. Methods: Moderated regression analysis was performed to verify the interaction effects of artistic characteristics on price. The moderating effects were studied by confirming the significance level of the interaction terms of the derived regression equation. In order to derive price estimation model, we use multiple linear regression analysis, which is a parametric statistical technique, and k-nearest neighbor (kNN) regression, which is a nonparametric statistical technique in machine learning methods. Results: Mostly, the influences of the price determinants of art are different according to the auction types and the artist 's reputation. However, the auction type did not control the influence of the genre of the work on the price. As a result of the analysis, the kNN regression was superior to the linear regression analysis based on the prediction accuracy. Conclusion: It provides a theoretical basis for the complexity that exists between pricing determinant factors of artworks. In addition, the nonparametric models and machine learning techniques as well as existing parameter models are implemented to estimate the artworks' price.

• 한국도로학회논문집
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• 제15권3호
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• pp.45-52
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• 2013

PURPOSES : This study is to construct the regression models of drainage asphalt concrete specimens and to provide the appropriate coefficients of hydraulic conductivity prediction models. METHODS: In terms of easy calculation of the hydraulic conductivity from porosity of asphalt concrete pavement, the estimation model of hydraulic conductivity was proposed using regression analysis. 10 specimens of drainage asphalt concrete pavement were made for measurement of the hydraulic conductivity. Hydraulic conductivity model proposed in this study was calculated by empirical model based on porosity and the grain size. In this study, it shows the compared results from permeability measured test and empirical equation, and the suitability of proposed model, using regression analysis. RESULTS: As the result of the regression analysis, the hydraulic conductivity calculated from the proposal model was similar to that resulted from permeability measured test. Also result of RMSE (Root Mean Square Error) analysis, a proposed regression model is resulted in more accurate model. CONCLUSIONS: The proposed model can be used in case of estimating the hydraulic conductivity at drainage asphalt concrete pavements in fields.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2005년도 학술발표논문집
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• pp.614-619
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• 2005

The object of this study was to presented regression equations for obtaining simply and quickly values of water quality items, BOD, COD, T-N, and T-P. Regression equations obtained to analyze relationships for water quality items to land use types in agricultural reservoir watersheds. In order to derive regression equations, a multiple linear regression analysis was used in this studying reservoirs. In this regression analysis, a independent values used land used types and dependent values used BOD, COD, T-N, T-P values in water quality items. The results showed that numbers of regression equation ranging above 0.90 in a multiple correlation coefficient (MCC) was not found, ranging from 0.70 to 0.90 in the MCC was 6, ranging from 0.40 to 0.70 in the MCC was 20, and ranging from 0.20 to 0.40 in the MCC was 4. The results of this study can be used as a basic information for evaluating simply and quickly water quality for proposing and designing steps in water quality policy.

• 대한인간공학회지
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• 제6권1호
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• pp.3-8
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• 1987

This paper develops a statistical mode which estimates mental and physical loads of light work from sinus arrhythmia (SA) scores. During experiments, various levels of mental and physical loads (respectively scored by information processing and finger tapping rates) were imposed on subjects and SA scores were measured from the subjects. Two methods were used in developing workload estimation model. One is an algebraic inverse function of a multivariate regression equation, where mental and physical loads are independent variables and SA scores are dependent variables. The other is a statistical multivariate inverse regression. Of the two methods, inverse function resulted in larger mean squqre error in predicting mental and physical loads. Hence, inverse regression model is recommended for precise workload estimation.