• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.4
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• pp.120-126
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• 1999

;The consicErations for reminder life of transmission line is gradually higher. It is requisite for investigation of ACSR's life to test tensile load of ACSR as a fundamental data. It is vary important to analysis correlations between results of tensile load testing and elasped years. Estimation of ACSR's life can be obtained by statistics processing using mechanical experirrental results. It is a general method to use regression analysis as a statistics processing technique. In this paper, we did experiment on tensile strength of ACSR by using a new and old ACSR as sample experirrental materials. The limit of life estimation is decided by basic line using twenty percentage reduction of rate tensile strength. This basic line is like to results of Canada Ontario Hydro-research. There are $95[\textrm{mm}^2]$, $97[\textrm{mm}^2]$, $120[\textrm{mm}^2]$, $240[\textrm{mm}^2]$ ACSRs which are experimented on this study. 1be life estimation of these ACSR is presented by table 1 to be obtained through the linear regression and nonlinear regression analysis. SPSS and statistics toolbox of matlab is used for analysis.lysis.

• Journal of Environmental Science International
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• v.24 no.6
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• pp.743-753
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• 2015

In this study, it is an object to develop a regression model for the estimation of TOC (total organic carbon) concentration using investigated data for three years from 2010 to 2012 in the Gam Stream unit watershed, and applied in 2009 to verify the applicability of the regression model. TOC and $COD_{Mn}$ (chemical oxygen demand) were appeared to be derived the highest correlation. TOC was significantly correlated with 5 variables including BOD (biological oxygen demand), discharge, SS (suspended solids), Chl-a (chlorophyll a) and TP (total phosphorus) of p<0.01. As a result of PCA (principal component analysis) and FA (factor analysis), COD, TOC, SS, discharge, BOD and TP have been classified as a first factor. TOCe concentration was estimated using the model developed as an independent variable $BOD_5$ and $COD_{Mn}$. R squared value between TOC and measurement TOC is 0.745 and 0.822, respectively. The independent variable were added step by step while removing lower importance variable. Based on the developed optimal model, R squared value between measurement value and estimation value for TOC was 0.852. It was found that multiple independent variables might be a better the estimation of TOC concentration using the regression model equation(in a given sites).

• The Journal of Sustainable Design and Educational Environment Research
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• v.11 no.2
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• pp.19-27
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• 2012

This study was carried out in order to establish the estimation equation for school power consumption using regression analysis based on collected power consumption for two years of weather data and schools are located in Central Changwon and Masan district in Changwon city. (1) The power consumption estimation equation for Heating and cooling is calculated using power consumption per unit volume, the difference between actual power consumption and results of estimation equations is 4.1%. (2) The power consumption estimation equation for heating load is showed 2.6% difference compared to actual power consumption in Central Changwon and is expressed 2.9% difference compared to that in Masan district. Therefore, the power consumption prediction for each school using the power consumption estimation equation is possible. (3) The power consumption estimation equation for cooling load is showed 8.0% difference compared to actual power consumption in Central Changwon and is expressed 2.9% compared to that in Masan district. As the power consumption estimation equation for cooling load is expressed difference compared to heating load, it needs to investigate influence for cooling load.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.505-513
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• 2017

Recently, numerous small area estimation studies have been conducted to obtain more detailed and accurate estimation results. Most of these studies have employed spatial regression models, which require a clear definition of spatial neighborhoods. In this study, we introduce the Delaunay triangulation as a method to define spatial neighborhood, and compare this method with the k-nearest neighbor method. A simulation was conducted to determine which of the two methods is more efficient in defining spatial neighborhood, and we demonstrate the performance of the proposed method using a land price data.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.98-103
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• 1997

Given the small bit allocation for motion information in very low bit-rate coding, motion estimation using the block matching algorithm(BMA) fails to maintain an acceptable level of prediction errors. The reson is that the motion model, or spatial transformation, assumed in block matching cannot approximate the motion in the real world precisely with a small number of parameters. In order to overcome the drawback of the conventional block matching algorithm, several triangle-based methods which utilize triangular patches insead of blocks have been proposed. To estimate the motions of image sequences, these methods usually have been based on the combination of optical flow equation, affine transform, and iteration. But the compuataional cost of these methods is expensive. This paper presents a fast motion estimation algorithm using a multiple linear regression model to solve the defects of the BMA and the triange-based methods. After describing the basic 2-D triangle-based method, the details of the proposed multiple linear regression model are presented along with the motion estimation results from one standard video sequence, representative of MPEG-4 class A data. The simulationresuls show that in the proposed method, the average PSNR is improved about 1.24 dB in comparison with the BMA method, and the computational cost is reduced about 25% in comparison with the 2-D triangle-based method.

• The Korean Journal of Food & Health Convergence
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• v.8 no.1
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• pp.21-30
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• 2022

This study proposed a multiple regression equation for predicting VO2max of elderly men and women using functional performance variables required to conduct daily activities. The subjects of this study were 58 elderly men (72.4±5.9 yrs) and 117 elderly women (73.4±4.5 yrs) aged 65-90 who belong to the senior welfare center. The maximal graded exercise test using a cycle ergometer and functional performance representing muscle strength, endurance, static and dynamic flexibility, mobility, and agility were measured. For statistical processing, multiple regression analysis was performed, and the statistical significance level was α = .05. As a result, the VO2max estimation formula for the elderly was 0.419 (standing up and sitting down a chair) + 0.199 (leg endurance against wall) + 5.383, and R2=0.406. In addition, the VO2max estimation formula for elderly women is - 0.737 (standing up from a supine position) - 0.144 (waking around two cones in a figure 8) - 0.135 (%body fat) + 0.042 (one leg balance with eyes open) + 29.395, R2=0.367 was calculated. The conclusion is that if the maximal graded exercise test is not available, it is considered that VO2max of the elderly can be predicted properly by using the estimation formula calculated based on the functional performance variable.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1095-1101
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• 2008

The desirable method to diagnose abnormal blood pressure is to measure and manage blood pressure continuously and regularly. However, the sphygmomanometers that are based on a cuff have faults in that they can not measure the blood pressure continuously and they cause an unpleasant feeling. Therefore, it is essential to develop a new measuring method that causes no pain and that can obtain blood pressure continuously without any unpleasant feeling. Thus, we propose here a regression method to estimate the systolic blood pressure by using the PTTL(pulse transit time on leg) with some body parameters which are chosen from the relational analysis with systolic blood pressure. The data we use to make the regression model were obtained in triplicate from each of 50 males who were from 18 to 35 years. And we made estimation experiments of blood pressure on 10 males who did not take part in the making the regression model. According to the results, the proposed method showed a mean error of 4.00 mmHg and the standard variance was 2.45 mmHg. When we comparing the results of the proposed method with the rule of American National Standards Institute of the Association of the Advancement of Medical Instruments(ANSI/AAMI), the results satisfied the rule of a mean error less than 5 mmHg and a standard variance less than 8 mmHg. Therefore we were able to validate the usefulness of the proposed method.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.737-746
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• 2013

The Bayesian method can be applied successfully to the estimation of the censored regression model introduced by Tobin (1958). The Bayes estimates show improvements over the maximum likelihood estimate; however, the performance of the Bayesian interval estimation is questionable. In Bayesian paradigm, the prior distribution usually reflects personal beliefs about the parameters. Such subjective priors will typically yield interval estimators with poor frequentist properties; however, an objective noninformative often yields a Bayesian procedure with good frequentist properties. We examine the performance of frequentist properties of noninformative priors for the Tobit regression model.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.1
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• pp.76-83
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• 2016

The various model tests are carried out to estimate and verify a ship performance in the design stage. But in view of the cost, the model test should be applied to every project vessel is very inefficient. Therefore, other methods of predicting the maneuverability with confined data are required at the initial design stage. The purpose of this study is to estimate the hydrodynamic derivatives by using the multiple regression analysis and PMM test data. The characteristics of the stern shape which has an important effect on the maneuverability are applied to the regression analysis in this study. The correlation analysis is performed to select the proper hull form coefficients and stern shape factors used as the variables in the regression analysis. The comparative analysis of estimate results and model test results is conducted on two ships to investigate the effectiveness of the maneuvering hydrodynamic derivatives estimation applied the stern shape. Through the present study, it is verified that the estimation using the stern shape factors as the variables are valid when the stern shape factors are located in the center of the database.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.2056-2069
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• 2014

In order to implement interactive and personalized Web services properly, it is necessary to understand the tangible and intangible responses of the users and to recognize their emotional states. Recently, some studies have attempted to build emotional state estimation models based on facial expressions. Most of these studies have applied multiple regression analysis (MRA), artificial neural network (ANN), and support vector regression (SVR) as the prediction algorithm, but the prediction accuracies have been relatively low. In order to improve the prediction performance of the emotion prediction model, we propose a novel SVR model that is optimized using a genetic algorithm (GA). Our proposed algorithm-GASVR-is designed to optimize the kernel parameters and the feature subsets of SVRs in order to predict the levels of two aspects-valence and arousal-of the emotions of the users. In order to validate the usefulness of GASVR, we collected a real-world data set of facial responses and emotional states via a survey. We applied GASVR and other algorithms including MRA, ANN, and conventional SVR to the data set. Finally, we found that GASVR outperformed all of the comparative algorithms in the prediction of the valence and arousal levels.