• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.71-77
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• 2012

This paper introduces the projection methods by nonlinear regression model. To predict the student numbers, a log model and an involution model as the kind of a trend-extrapolation method are used. Empirical evidence shows that a projection by log model is better than by involution model with the confidence interval estimations for the coefficients of determination.

• Korean Institute of Interior Design Journal
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• v.13 no.5
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• pp.198-205
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• 2004

The remodeling of apartment that improves the improves the life level is going to be in the market because of lots of old apartment buildings. Until now, the research of remodeling is mainly restricted to the laws and financial funding, however, the needs in the trend of remodeling. This research, first, through the examples of remodeling in the country, this study draws remodeling factors that can be applied. Secondly, this study targets the study of remodeling to apartments and analyzes the type of housings made by the Korea National Housing Corporation. Thirdly the study analyzes the features that appear in housing units and draws out factors of remodeling This research's result is arranged as follows. \circled1Need Remodeling thorough study of space expanded, grant between artificer and active performance improvement direction such as building equipment expansion along with Remodeling concept of unit repair. \circled2When apartments are newly built, systematic construction is necessary that considers future efficiency improvement from the design stage. \circled3This study, which applied the characteristic factors appearing after the 1990s to remodeling factors, show that they can be applied when remodeling the worn out wall-slab type apartments.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1167-1173
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• 2011

The goal of this paper is to suggest an algorithm to get forecasting for the numbers of students in the city or county in local government by using the double exponential smoothing method. By 2044 year, the third year of high school students in the Chilgok, Gumi, Gyeongsan, Andong, Pohang and Gimchen are reduced about 40-70%, the those of in the remaining city or county are reduced about 70-95%. In conclusion, the forecasting numbers of students of the 23 counties in Kyungbuk Province are on the decrease to 40%-100% until 2044 year in comparison with the numbers of students on 2010 years.