• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.27-29
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• 2023

불안정한 부동산 가격은 지속적인 사회 문제로 거론되고 있는데 이는 부동산 매매 가격을 예측할 수 있는 정확한 지표가 체계적이고 구체적으로 확립되지 않았기 때문이다. 본 논문은 가격변동에 주요하게 영향을 미치는 특성을 파악하여 가격 예측 지표로 활용하기 위해 머신러닝 모델을 적용하여 특성 분석을 수행한다. 이를 위해 한국부동산원에서 제공하는 2021년 10월부터 2022년 9월까지 1년간의 역 주변 500M 이내 거래 데이터 약 30만 6천 개를 어떠한 과정으로 전처리하여 머신러닝 모델에 적용하였는지 기술한다.

• Korean Journal of Veterinary Research
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• v.55 no.2
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• pp.125-131
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• 2015

A total of 11,395 animals were impounded in shelters in Seoul in 2013. The Animal Protection Division of the Seoul metropolitan government has annual contracts with local veterinary associations as well as Korean animal rescue and management organizations for providing shelter to animals, and collects monthly statistics from these groups. In 2013, the collected intake and outcome data for 25 districts were reviewed to analyze shelter capacity in terms of housing capacity (monthly daily average intake, required holding capacity, and adoption-driven capacity), staff capacity (staff hours required for daily care), and live release rate. Seasonal variations in the monthly daily average intake were observed, indicating that management of these shelters requires various strategies. This study was performed to analyze and interpret meaningful statistics for improving the efficiency of animal shelters in Seoul. However, inconsistent collection of animal statistics limited data compilation. Creation of a basic animal statistics matrix with reference to well-designed matrices from recognized professional animal shelters is essential. These complied statistical data will help plan for future animal shelter needs in Seoul.

• Journal of the Korean housing association
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• v.16 no.3
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• pp.101-107
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• 2005

The reason that compulsory removals of a low-quality housing redevelopment such as involuntary or unintentional migration present a problem for urban communities is that whether involuntary movers adapt themselves to their new home has an influence on the urban communities that surround them. Moreover, involuntary emigrants have higher probability of choosing faulty residential areas than voluntary emigrants do. This gives rise to a problem of another residential migration for involuntary movers. In order to solve these problems, there is a need for a new housing policy that enables original residents to come back to their old community. However studies for resettlement had not conducted subjects about housing redevelopment characteristics which influences the involuntary movers directly. Instead personal microscopic characteristics such as statistics of resettlement, the moving distance, the reason of moving, improvement of living environment, had been main subjects of farmer studies. So the purpose of this study is to analyze an analysis of the relationship between resettlement and housing redevelopment characteristics. The data used in this study was obtained at 47 areas designated by Seoul (metropolis) since 1990 for redevelopment. Cluster Analysis Is used for dividing high rate of resettlement with low rate of resettlement and Regression Analysis is used for the analysis of the relationship between resettlement and housing redevelopment characteristics. The results of examining the effects of a redeveloped housing complex on returning residents at 47 areas designated by Seoul (metropolis) since 1990 fur redevelopment are as follows: First, A housing complex with a high returning rate (remove-in rate?) has no state/public land, unauthorized building owners who are in the low-income brackets, and few interested parties such as union members. This is the characteristic of a redeveloped housing complex with a short-period project span. On the contrary, a housing complex that has a low returning rate is crowded by state/public land, and numerous unauthorized building owners, and interested parties. Second, According to the linear regression analysis, among the factors that affect returning residents, 'physical properties(characteristics) of a region', 'population properties within a region', and 'properties of a project span' indicate a negative(-)influence whereas 'properties of a complex density' shows a positive(+) influence. In a nutshell, the more the physical properties, population properties, projectspan properties, the lower the returning rate and the more the complex density properties, the higher the returning rate. In detail, an area with many small land and new/large buildings, a high population, and a long project duration has a low returning rate of original residents while an area holding large capacity and buildings with many number of floors (multiple-storied building) has a high returning rate.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.891-908
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• 2010

In Korea, the small area estimation method is currently unpopular in generating o cial statistics. Because it may be difficult to determine the reliability for small area estimation, although small area estimation ha a sufficiently good advantage to generate small area statistics for Korea. This paper inspects the method of making small area unemployment through the small area estimation method. To estimate small area unemployment we used an EBLUP-type estimator based on a logistic linear mixed model. To evaluate the EBLUP-type estimator we accomplished the real data analysis and simulation experiment from the population and housing census data. In addition, small area estimates are compared to large sample survey estimates. We found the provided method in this paper is highly recommendable to generate small area unemployment as the official statistics.

• Korean Journal of Construction Engineering and Management
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• v.12 no.6
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• pp.110-119
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• 2011

Global warming caused by excessive greenhouse gas emission is causing climate change all over the world. In Korea, greenhouse gas emission from residential buildings accounts for about 10% of gross domestic emission. Also, the number of deteriorated multi-family housing complexes is increasing. Therefore, the goal of this research is to establish the bases to manage energy consumption continuously and methodically during MR&R period of multi-family housings. The research process and methodologies are as follows. First, research team collected the data on project characteristics and energy consumption of multi-family housing complexes in Seoul. Second, an ontology-based breakdown structure was established with some primary characteristics affecting the energy consumption, which were selected by statistical analysis. Finally, a predictive model of energy consumption was developed based on the ontology-based breakdown structure, with application of CBR, ANN, MRA and GA. In this research, PASW (Predictive Analytics SoftWare) Statistics 18, Microsoft EXCEL, Protege 4.1 were utilized for data analysis and prediction. In future research, the model will be more continuous and methodical by developing the web-base system. And it has facility manager of government or local government, or multi-family housing complex make a decision with definite references regarding moderate energy consumption.

• Journal of Korean Home Economics Education Association
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• v.20 no.4
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• pp.59-75
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• 2008

This study is designed to support the development and the teaching of revised curriculum of 2007 "Technology & Home Economics" by investigating the actual condition and the necessity of education for elderly housing education. Questionnaire survey was conducted with 488 high school students in Gyeongnam in 2008. The data analyzed by descriptive statistics, t-test, One-way ANOVA, Duncan's multiple range test by using SPSS 14 program. The results showed that most of the students were dissatisfied with their middle school education of elderly housing due to the lack of interesting and practical contents. Thus, various teaching-learning methods where student can experience and experiment is needed. Also, the students demanded more of factors of elderly housing, spacing plan, elderly welfare service and less of three-generation housing and senior housing in their elderly housing education. The needs of education contents differed among students depending on variables such as sex, graduated middle school, household income, dwelling space and length of residential years. Therefore, revised 2007 curriculum of "Technology & Home Economics" should include required contents in related chapters. Because there are significant differences among textbooks about elderly housing, further attention needs to be paid to the new textbooks in order to include education contents evenly. At the same time, teachers should organize their teaching contents considering the divergence of variables. The effect of elderly housing education will be maximized if the revised curriculum consists of more experimental activities such as elderly simulation in the local community.

• Journal of Families and Better Life
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• v.28 no.2
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• pp.27-37
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• 2010

The purpose of the study was to analyze the constraints that are normally experienced before moving in the context of the household characteristics of households that had recently moved to newly-built apartments. The data for the analysis was collected through a self-administered questionnaire from July 1, 2008 to August 10, 2008. The sample consisted of 251 households in Ulsan living in an apartment complex who had moved within a year. The data from the sample was analyzed by descriptive statistics, factor analysis, and analysis of variance with Duncan's multiple range tests. The results are as follows. The constraints were categorized into information gathering, attractive housing characteristics, expectations of residential mobility, housing development and policies, and resources. Overall, the constraints did not have a huge impact on the performance of the residential mobility of the sample households. Resources, however, were the most influential factors among the five constraints followed by attractive housing characteristics, information gathering, etc. The constraints varied based on the demographic characteristics, such as the household size, duration of marriage, age of the household head, and the socio-economic characteristics, such as the education level of the household head, household income, and the number of mobility. As the number of family members increased, the age of the household head went up, or the level of education went down, the constraints on information gathering were affected in terms of performing residential mobility. Households with a middle aged head with a professional occupation were more constrained by the attractive characteristics of the housing. The impact of the resources related constraints was significantly different based on the number of family members, marriage duration, and the household head's age and occupation, and the number of mobility.

• KIEAE Journal
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• v.14 no.5
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• pp.103-109
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• 2014

Apartment housing should require the systematic maintenance to provide the decent living condition during its life. Each household should participate the maintenance activities and pay for the repair. Therefore, the required cost for repair would be needed to plan in the repair schedule because each household could not pay the much repair money at a time. After apartment constructed, a long term repair plan would be prepared in repair time, repair scope and a required cost. A few studies are said that the repair cost depends on the building deterioration, elapsed year and management factors. The above factors are not be certain to affect the repair management while it may be important to prepare the required money and the repair time. In this paper, it aimed at analyzing the correlation between the repair management and the management factors, especially total area, number of household. This would educe the unit cost per number of household and management area in the individual boiler and elevator with full change and full repair. The unit cost per number of household and area for full change are about 199,000 won/household and $1,954won/m^2$ in the individual boiler respectively. The unit cost of the elevator for full change is 94,000 won/household and $5,429won/m^2$ respectively. Second, this study shows that the elapsed year after construction would not be related the repair unit cost.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2953-2966
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• 2018

Housing prices are closely related to various variables that indicate macroeconomic conditions. In this paper, empirical analysis based on data is performed referring to previous studies. Focusing on the policy interest rate among the factors affecting the housing price, the non-linear impulse responses of other variables to the interest rate shock are analyzed. Using the random forest algorithm, the variable importance scores of the macroeconomic variables presented in the previous studies are calculated. After selecting the variables through this process, the impulse responses are calculated using a model that can capture non-linearity. According to the model, the responses of housing prices to the policy rate is only significant when the rate is raised. Especially, the impulse response is amplified when the shock increases due to the non-linear characteristics that can not be captured by the traditional VAR methodology. The analysis results suggest that the interest rate as a policy instrument should be approached from a more cautious perspective.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.117-134
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• 2024

Housing is an essential element of human living environments. The type of housing occupancy can vary based on age, family composition, occupation, education level, and economic situation. In this study, we used social survey statistics to investigate the relationship between housing ownership types and individual and societal characteristics. The research findings revealed that apartment residency rates were high across all age groups. Married individuals tended to have higher apartment residency rates compared to unmarried individuals. Additionally, as the number of household members and generations increased, so did the likelihood of apartment residency. Overall, higher income levels and stable employment were associated with a preference for homeownership. However, there was no significant correlation between homeownership and education level or employment status. National and local authorities should focus on housing supply that aligns with the purchasing capacity and characteristics of potential homebuyers.