• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1483-1490
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• 2004

To accomplish a project successfuly, we have to estimate develpment effort accurately. But, development effort is different to software size and operation environment. Usually, we made use of function point for estimating development effort. In this paper. we make use of 789 project data. It is related to development projects in 1990`s. We investigate the variable affecting development effort. Also, we exedcute multiple liner regression analysis for looking linear relation about variables. We find the regression equation for multistage by dividing PDR that influ-enced development effort step by step.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.221-228
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• 2011

For service-area-widening and commercialization of DGNSS service, Ministry of Land, Transport and Maritime Affairs is developing a DGNSS service based on VRS using T-DMB. In this study, three PRC generation algorithms are developed for VRS DGNSS and their accuracies were evaluated. Three DGNSS correction generation algorithms are based on inverse distance weighting, 1st- and 2nd- multiple linear regression, and their positioning accuracies were compared in terms of the number of reference stations used for network composition and the algorithm type. As a result, the positioning accuracy of the case of using 16 sites is better than that of 6 sites. And the algorithm using the multiple linear regression showed the best performance. When the positioning accuracy of VRS DGNSS was compared with the traditional single-reference DGNSS, the improvement ratio was 20-23% and 20-36% for the horizontal and vertical directions, respectively.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.365-377
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• 2020

We discuss latent factor regression when constructing a common structure inherent among explanatory variables to solve multicollinearity and use them as regressors to construct a linear model of a response variable. Bayesian estimation with LASSO prior of a large penalty parameter to construct a significant factor loading matrix of intrinsic interests among infinite latent structures. The estimated factor loading matrix with estimated other parameters can be inversely transformed into linear parameters of each explanatory variable and used as prediction models for new observations. We apply the proposed method to Product Service Management data of HBAT and observe that the proposed method constructs the same factors of general common factor analysis for the fixed number of factors. The calculated MSE of predicted values of Bayesian latent factor regression model is also smaller than the common factor regression model.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.182-182
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• 2015

우리나라에서는 강우관측시스템의 지역적 불균형으로 상대적으로 소규모 저수지의 경우 미계측유역의 특성을 가지며, 신뢰성 있는 강우량, 유출량, 증발량 자료가 매우 부족한 실정이다. 다목적댐 유역과 같은 계측유역의 경우 상류유역의 유입량 자료의 확보가 용이하지만 대부분의 유역의 경우 계측장비가 부족하여 신뢰성이 확보된 유입량 자료를 얻는데 많은 어려움이 있다. 본 연구에서는 미계측유역의 유입량 산정을 위하여 계측유역을 대상으로 강우-유출 모형의 매개변수를 산정하였으며, 산정된 매개변수를 유역특성인자와의 상관성을 토대로 다중선형회귀분석기법(multiple linear regression, MLR)을 적용하여 지역화(regionalization)를 위한 회귀식을 도출하였다. 이를 위해 양질의 유량자료가 확보된 K-water 17개 댐 유역을 대상으로 매개변수를 산정하였으며 이 중 2개의 댐 유역을 미계측유역으로 간주하여 개발된 모형을 검증하였다. 대부분의 통계 지표에서 우수한 모의능력을 확인하였으며, 본 연구를 통하여 개발된 지역화 기법을 미계측유역에 활용한다면 보다 정량적이고 효율적인 수자원 계획이 가능할 것으로 판단된다. 향후 연구로는 불확실성을 고려한 Bayesian GLM 모형을 이용한 지역화기법을 개발하여 매개변수의 불확실성까지 고려할 수 있는 방안을 모색하고자 한다.

• Journal of the Korean Chemical Society
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• v.38 no.3
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• pp.221-223
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• 1994

We tried to apply the linear solvation energy comparison method to solute retention in normal phase liquid chromatography. Correlation coefficients of regression of lnk' collected in a fixed eluent against solute polarity indices have proven to be lower than those obtained from reversed phase liquid chromatography data. This event can be attributed to complexity of solute retention process in normal phase liquid chromatography. We concluded from the regression results that each specific polarity of the stationary phase is greater than that of the mobile phase and that the difference in each polarity between the stationary phase and the mobile phase decreases as the volume fraction(${\phi}$) of the more polar solvent in the mobile phase increases. Correlations of lnk' of a single solute against solvent polarity indices have proven to be meaningless owing to covariance among the solvent polarity indices. Instead, a good linear relationship between lnk' and solvent ${\pi}^*$ was observed, and its linearity is better than that between lnk' and ${\phi}$.

• Journal of Korea Water Resources Association
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• v.42 no.6
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• pp.465-480
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• 2009

In this study, single and multiple linear regression model were used to derive the relationship between precipitation and altitude, latitude and longitude in Jejudo. The single linear regression analysis was focused on whether orographic effect was existed in Jejudo by annual average precipitation, and the multiple linear regression analysis on whether orographic effect was applied to each duration and return period of quantile from regional frequency analysis by index flood method. As results of the regression analysis, it shows the relationship between altitude and precipitation strongly form a linear relationship as the length of duration and return period increase. The multiple linear regression precipitation estimates(which used altitude, latitude, and longitude information) were found to be more reasonable than estimates obtained using altitude only or altitude-latitude and altitude-longitude. Especially, as results of spatial distribution analysis by kriging method using GIS, it also provides realistic estimates for precipitation that the precipitation was occurred the southeast region as real climate of Jejudo. However, the accuracy of regression model was decrease which derived a short duration of precipitation or estimated high region precipitation even had long duration. Consequently the other factor caused orographic effect would be needed to estimate precipitation to improve accuracy.

• Analytical Science and Technology
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• v.28 no.3
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• pp.187-195
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• 2015

The heat of sublimation (HOS) is an essential parameter used to resolve environmental problems in the transfer of organic contaminants to the atmosphere and to assess the risk of toxic chemicals. The experimental measurement of the heat of sublimation is time-consuming, expensive, and complicated. In this study, quantitative structural property relationships (QSPR) were used to develop a simple and predictive model for measuring the heat of sublimation of organic compounds. The population-based forward selection method was applied to select an informative subset of descriptors of learning algorithms, such as by using multiple linear regression (MLR) and the support vector machine (SVM) method. Each individual model and consensus model was evaluated by internal validation using the bootstrap method and y-randomization. The predictions of the performance of the external test set were improved by considering their applicability to the domain. Based on the results of the MLR model, we showed that the heat of sublimation was related to dispersion, H-bond, electrostatic forces, and the dipole-dipole interaction between inter-molecules.

• Journal of Industrial Convergence
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• v.20 no.12
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• pp.179-186
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• 2022

This study aims to develop a predictive model to suggest a used sales price to sellers and buyers when trading used tablet PCs. For model development, we analyzed the real used tablet PC transaction data and additionally collected detailed product information. We developed several predictive models and selected the best predictive model among them. Specifically, we considered a multiple linear regression model using the used sales price as a dependent variable and other variables in the integrated data as independent variables, a multiple linear regression model including interactions, and the models from stepwise variable selection in each model. The model with the best predictive performance was finally selected through cross-validation. Through this study, we can predict the sales price of used tablet PCs and suggest appropriate used sales prices to sellers and buyers.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.5
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• pp.502-508
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• 2012

Quantitative ultrasound technologies for osteoporosis diagnosis measure ultrasonic parameters such as speed of sound(SOS) and normalized broadband ultrasound attenuation(nBUA) in the calcaneus (heel bone). In the present study, the dependences of SOS and nBUA on bone mineral density in the proximal femur with high risk of fracture were investigated by using 20 trabecular bone samples extracted from bovine femurs. SOS and nBUA in the femoral trabecular bone samples were measured by using a transverse transmission method with one matched pair of ultrasonic transducers with a center frequency of 1.0 MHz. SOS and nBUA measured in the 20 trabecular bone samples exhibited high Pearson's correlation coefficients (r) of r = 0.83 and 0.72 with apparent bone density, respectively. The multiple regression analysis with SOS and nBUA as independent variables and apparent bone density as a dependent variable showed that the correlation coefficient r = 0.85 of the multiple linear regression model was higher than those of the simple linear regression model with either parameter SOS or nBUA as an independent variable. These high linear correlations between the ultrasonic parameters and the bone density suggest that the ultrasonic parameters measured in the femur can be useful for predicting the femoral bone mineral density.

• Journal of the Korea Society for Simulation
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• v.21 no.3
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• pp.79-88
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• 2012

Recently, the study in efficient operation, maintenance, and equipment-design have been growing rapidly in military industry to meet the required missions. Through out these studies, the importance of Concurrent Spare Parts(CSP) are emphasized. The CSP, which is critical to the operation and maintenance to enhance the availability, is offered together when a equipment is delivered. Despite its significance, th responsibility for determining the range and depth of CSP are done from administrative decision rather than engineering analysis. The purpose of the paper is to optimize the number of CSP per item using simulation and multiple regression. First, the result, as the change of operational availability, was gained from changing the number of change in simulation model. Second, mathematical regression was computed from the input and output data, and the number of CSP was optimized by multiple regression and linear programming; the constraint condition is the cost for optimization. The advantage of this study is to respond with the transition of constraint condition quickly. The cost per item is consistently altered in the development state of equipment. The speed of analysis, that simulation method is continuously performed whenever constraint condition is repeatedly altered, would be down. Therefore, this study is suitable for real development environment. In the future, the study based on the above concept improves the accuracy of optimization by the technical progress of multiple regression.