• ICROS
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• v.15 no.4
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• pp.19-27
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• 2009

최근에는 여름철 냉방부하가 현격하게 증가하고 있는 상황에서, 일사량 특성공선과 부하특성곡선의 유사성을 이용하여 여름철에 상호보완효과를 얻을 수 있는 태양광발전방식의 보급 활성화는 에너지 소비 측면에서도 매우 바람직하다 할 수 있다.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.113-123
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• 2012

This study introduces a new type of a modal split model that use zonal data instead of cost data as independent variables. It has been indicated that the ones using cost data have deficiencies in the multicollinearity of travel time and cost variables and unpredictability of independent variables. The zonal data employed in this study include (1) socioeconomic data, (2) land use data and (3) transportation system data. The test results showed that the proposed modal split model using zonal data performs better than the other does.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.321-328
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• 2009

In regression analysis, the ordinary least squares estimates of regression coefficients become poor, when the correlations among predictor variables are high. This phenomenon, which is called multicollinearity, causes serious problems in actual data analysis. To overcome this multicollinearity, many methods have been proposed. Ridge regression, shrinkage estimators and methods based on principal component analysis (PCA) such as principal component regression (PCR) and latent root regression (LRR). In the last decade, many statisticians discussed sensitivity analysis (SA) in ordinary multiple regression and same topic in PCR, LRR and logistic principal component regression (LPCR). In those methods PCA plays important role. Many statisticians discussed SA in PCA and related multivariate methods. We introduce the method of PCR and LRR. We also introduce the methods of SA in PCR and LRR, and discuss the properties of SA in PCR and LRR.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.577-588
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• 2014

The collection and storage of a large volumes of data are becoming easier; however, the number of variables is sometimes more than the number of samples(objects). We now face the problem of dependency among variables(such as multicollinearity) due to the increased number of variables. We cannot apply various statistical methods without satisfying independency assumption. In order to overcome such a drawback we consider a categorizing (or discretizing) observations. We have a data set of nancial indices from banks in Korea that contain 78 variables from 16 banks. Genetic sequence data is also a good example of a large data and there have been numerous statistical methods to handle it. We discover lots of useful bank information after we transform bank data into categorical data that resembles genetic sequence data and apply bioinformatic techniques.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.531-539
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• 2009

Logistic regression is widely used as a datamining technique for the customer relationship management. The maximum likelihood estimator has highly inflated variance when multicollinearity exists among the regressors, and it is not robust against outliers. Thus we propose the robust principal components logistic regression to deal with both multicollinearity and outlier problem. A procedure is suggested for the selection of principal components, which is based on the condition index. When a condition index is larger than the cutoff value obtained from the model constructed on the basis of the conjoint analysis, the corresponding principal component is removed from the logistic model. In addition, we employ an algorithm for the robust estimation, which strives to dampen the effect of outliers by applying the appropriate weights and factors to the leverage points and vertical outliers identified by the V-mask type criterion. The Monte Carlo simulation results indicate that the proposed procedure yields higher rate of correct classification than the existing method.

• Korean Journal of Construction Engineering and Management
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• v.16 no.5
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• pp.77-85
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• 2015

The Hedonic Pricing model is the predominant approach used today to model the effect of relevant factors on real estate prices. These factors include intrinsic elements of a property such as floor areas, number of rooms, and parking spaces. Also, The model also accounts for the impact of amenities or undesirable facilities of a property's value. In the latter case, euclidean distances are typically used as the parameter to represent the proximity and its impact on prices. However, in situations where multiple facilities exist, multi-colinearity may exist between these parameters, which can result in multi-regression models with erroneous coefficients. This research uses Variance Inflation Factors(VIF) and Ridge Regression to identify these errors and thus create more accurate and stable models. The techniques were applied to apartments in Guro-gu of Seoul, whose prices are impacted by subway stations as well as a public prison, a railway terminal and a digital complex. The VIF identified colinearity between variables representing the terminal and the digital complex as well as the latitudinal coordinates. The ridge regression showed the need to remove two of these variables. The case study demonstrated that the application of these techniques were critical in developing accurate and robust Hedonic Pricing models.

• Proceedings of the International Microelectronics And Packaging Society Conference
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• 1999.11a
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• pp.67-74
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• 1999

• Proceedings of the KSR Conference
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• 2006.05b
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• pp.515-521
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• 2006

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.6
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• pp.726-735
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• 2003

A Process of 3-D Particle image velocimetry, called here, as '3-D volume PIV' was developed for the full-field measurement of 3-D complex flows. The present method includes the coordinate transformation from image to camera, calibration of camera by a calibrator based on the collinear equation, stereo matching of particles by the approximation of the epipolar lines, accurate calculation of 3-D particle positions, identification of velocity vectors by 3-D cross-correlation equation, removal of error vectors by a statistical method followed by a continuity equation criterior, and finally 3-D animation as the post processing. In principle, as two frame images only are necessary for the single instantaneous analysis 3-D flow field, more effective vectors are obtainable contrary to the previous multi-frame vector algorithm. An Experimental system was also used for the application of the proposed method. Three analog CCD camera and a Halogen lamp illumination were adopted to capture the wake flow behind a bluff obstacle. Among 200 effective particle s in two consecutive frames, 170 vectors were obtained averagely in the present study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.3 no.2
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• pp.39-47
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• 1985

This study analyzes space resection and space intersection for terrestrial convergent photos taken on the straight line and the circular line by collinearity condition. The purpose is to investigate the properties of convergent case, and to suggest the optimum angle of convergence. Accuracies at convergent angles less than 20$^\circ$ are lower than those in normal photos, but by changing from 20$^\circ$to 90$^\circ$ the accuracy is improving with the highest at 90$^\circ$ convergence. Also, convergent photos on circular line is far higher than those on straight line in accuracies of results, therefore it is expected to apply this results effectively for precise analysis of various facilities.