• 한국산학기술학회논문지
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• 제14권10호
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• pp.4876-4883
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• 2013

본 연구는 한옥보전 구역 내에서 비주거용 한옥이 점차 늘어나고 있는 상황에서 비주거한옥에 대한 제도적 지원이 필요한 근거를 제시하는데 목적이 있다. 이를 위해 비주거한옥 제도적 지원의 필요성에 영향을 미치는 요인을 분석하여 비주거한옥의 가치를 평가하였다. 분석에는 로지스틱분석을 활용하였으며, 비주거한옥에 대한 제도적 지원 필요성에 동의하는 경우 어떠한 가치요인을 중요하게 판단하였는지 분석하였다. 분석결과, 주거환경이 열악한 한옥의 활용, 한옥 외관상 가치, 지역의 생활복지 서비스 제공, 관광객 수용, 상업공간 제공, 역사성 부족, 한옥에 대한 개방성 강화 등의 7개의 요인이 비주거한옥에 대한 제도적 지원 필요성 결정에 영향을 미치는 것으로 나타났다.

• 대한토목학회논문집
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• 제41권4호
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• pp.449-459
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• 2021

농업용 저수지의 80 % 이상이 50년 이상 된 노후 시설물로 안전성 및 기능 저하가 발생하고 있다. 이로 인해 저수지의 붕괴 등 안전사고가 발생하고 있는 실정이다. 이에 따라서 저수지의 붕괴 등의 안전사고를 미연에 방지하고자 정밀안전진단을 실시하고 우선순위에 따라 수리시설개보수사업을 시행하고 있다. 하지만 사업 우선순위 선정의 대부분은 시설물 관리자의 주관적인 판단을 통해 이루어지고 있다. 이에 본 연구에서는 정밀안전진단 결과 및 기존의 수리시설 개보수사업의 의사결정 사례를 D/B화하여 80개의 가설을 설정하고 상관분석 및 유의성검정을 통해 45개의 변수를 선정하였다. 선정된 변수들을 로지스틱회귀분석을 이용하여 의사결정지원모델을 제시하였다. 의사결정지원모델의 변수는 총 21개가 채택되었으며 모델의 분류 정확도는 86.8 %로 나타났다. 본 연구는 수리시설개보수사업 선정을 위한 의사결정의 정량적인 지표를 제시 한 부분에 중요한 의의를 가진다.

• Geomechanics and Engineering
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• 제34권3호
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.

• 한국경영과학회지
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• 제30권1호
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• pp.55-74
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• 2005

Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper employs a relatively new machine learning technique, support vector machines (SVMs). to bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use grid search technique using 5-fold cross-validation to find out the optimal values of the parameters of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM. we compare its performance with multiple discriminant analysis (MDA), logistic regression analysis (Logit), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• Journal of the Korean Data and Information Science Society
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• 제15권3호
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• pp.565-574
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• 2004

Classification tree algorithms including as CART by Brieman et al.(1984) in some aspects, recursively partition the data space with the aim of making the distribution of the class variable as pure as within each partition and consist of several steps. SUPPORT(smoothed and unsmoothed piecewise-polynomial regression trees) method of Chaudhuri et al(1994), a weighted averaging technique is used to combine piecewise polynomial fits into a smooth one. We focus on applying SUPPORT to a binary class variable. Logistic model is considered in the caculation techniques and the results are shown good classification rates compared with other methods as CART, QUEST, and CHAID.

• 대한안전경영과학회지
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• 제7권1호
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• pp.199-210
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• 2005

Customer segmentation prediction has attracted a lot of research interests in previous literature, and recent studies have shown that artificial neural networks (ANN) method achieved better performance than traditional statistical ones. However, ANN approaches have suffered from difficulties with generalization, producing models that can overfit the data. This paper employs a relatively new machine learning technique, support vector machines (SVM), to the customer segmentation prediction problem in an attempt to provide a model with better explanatory power. To evaluate the prediction accuracy of SVM, we compare its performance with logistic regression analysis and ANN. The experiment results with real data of insurance company show that SVM superiors to them.

• Communications for Statistical Applications and Methods
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• 제31권2호
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• pp.235-246
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• 2024

In high-dimensional data analysis, sufficient dimension reduction (SDR) has been considered as an attractive tool for reducing the dimensionality of predictors while preserving regression information. The principal support vector machine (PSVM) (Li et al., 2011) offers a unified approach for both linear and nonlinear SDR. This article comprehensively explores a variety of SDR methods based on the PSVM, which we call principal machines (PM) for SDR. The PM achieves SDR by solving a sequence of convex optimizations akin to popular supervised learning methods, such as the support vector machine, logistic regression, and quantile regression, to name a few. This makes the PM straightforward to handle and extend in both theoretical and computational aspects, as we will see throughout this article.

• 보건행정학회지
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• 제23권2호
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• pp.162-175
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• 2013

Background: The purpose of this study was to analyze the association between social support, psychosocial factors, and health behaviors of old adults in korean society. Methods: The data which was used in this study was extracted from the second wave of the Korean longitudinal study of aging in 2008. A total of 3,978 elderly aged 65 years or older were included in this study. We conducted $X^2$-test, t-test for the elderly health behavior in accordance with their social support and psychosocial factors. Also, multivariate logistic regressive analysis was performed in order to find how degree social support and psychosocial factors are associated with health behavior after adjusting sex, age, smoking (alcohol drinking), and other significant variables. The data was processed by SAS ver. 9.1 and Stata SE ver. 11. Results: Social support in older adults was significantly associated with lower smoking, alcohol drinking, exercise, and eating habit. Also, psychosocial factors were positively associated with smoking, alcohol drinking, regular exercise, and eating habit. Conclusion: health behaviors of old adults are likely to be vulnerable to social support and psychosocial factors. To increase effectiveness of the health policy for the elderly in Korea, it is important to adapt new strategy to include the empowerment of elderly's social networks, policy support to enhance subjective expectation, and life satisfaction.

• 기본간호학회지
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• 제15권1호
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• pp.71-79
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• 2008

Purpose: The purpose of this study was to identify effects of family support and quality of life on smoking cessation in patients with coronary artery disease. Method: Data were collected using a self-reported questionnaire included smoking history, family support and quality of life (QOL). The participants were 159 male patient with coronary artery disease who were current smokers or ex-smokers. A logistic model was developed to estimate the likelihood of current smoker or ex-smoker. Results: Of the participants, 28.3% were current smokers and 71.7% were ex-smokers. The mean score for family support was 27.41 for positive support and 23.11 for negative support. The mean score for QOL was 50.48. There were significant differences in QOL according to smoking status. The predictors of smoking cessation were social interaction QOL and self-control QOL, and duration of smoking. The model correctly classified 89.5% of ex-smokers and 44.4% of current smokers and the correct classification for the total was 76.8%. Conclusion: Social interaction QOL, self-control QOL and duration of smoking were significant variables in prediction of smoking cessation. QOL should be considered in developing smoking cessation interventions. It is advisable to also examine the mediating effect of family support on quality of life.

• 보건행정학회지
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• 제32권2호
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• pp.180-189
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• 2022

Background: Social support contributes directly and indirectly to maintaining physical, mental, and social well-being. The aim of the study was to identify the impact of social support on self-rated health among Korean industrial accident workers. Methods: This study used data from the panel study of workers' compensation insurance (PSWCI). The final subjects were 2,759 workers who responded to a 2018 to 2020 PSWCI. Social support was defined as social contact with friends, neighbors, family, and social participation activities like religious activity, social activity, and club activity. Multivariate logistic regression analysis was performed to investigate causal relationships between social support and self-rated health using a generalized estimating equation model. Results: Proportion of workers' good self-rated health steadily increased (2018: n=1,447, 63.2%; 2019: n=1,542, 66.2%; 2020: n=1,653, 67.3%). Higher levels of social contacts with friend (worse: reference; same: β=0.442) and higher levels of social activity (yes: reference; no: β=-0.173) were especially associated with good self-rated health. Conclusion: This study confirmed social support positively influenced self-rated health among the self-rated health of industrial injured workers. The results of this study suggested that recovery policies that the government served should include programs enhancing social support for improving health among industrial injured workers.