• Proceedings of the Korea Database Society Conference
• /
• 1999.06a
• /
• pp.415-421
• /
• 1999

Altman의 연구(1965, 1977)나 Beaver의 연구(1986)와 같은 전통적 예측모형은 분석자의 판단에 따른 예측도가 높은 재무비율을 선정하여 다변량판별분석(MDA： multiple discriminant analysis), 로지스틱회귀분석 등과 같은 통계기법을 주로 이용해 왔으나 1980년 후반부터 인공지능 기법인 귀납적 학습방법, 인공신경망모형, 유전모형 둥이 부실기업예측에 응용되기 시작했다. 최근 연구에서는 인공신경망을 활용한 변수 및 모형개발에 관한 보고가 있다. 그러나 지금까지의 연구가 주로 기업의 재무적 비율지표를 고려한 모형에 치중되었으며 정성적 자료인 비재무지표에 대한 검증과 선정이 자의적으로 이루어져온 경향이었다. 또한 너무 많은 입력변수를 사용할 경우 다중공선성 문제를 유발시킬 위험을 내포하고 있다. 본 연구에서는 부실기업예측모형을 수립하기 위하여 정량적 요인인 재무적 지표변수와 정성적요인인 비재무적 지표변수를 모두 고려하였다. 재무적 지표변수는 상관분석 및 요인분석들을 통하여 유의한 변수들을 도출하였으며 비재무적 지표변수는 조직생태학내에서의 조직군내 조직사멸과 관련된 생태적 과정에 대한 요인들 중 조직군 내적요인으로 조직의 연령, 조직의 규모, 조직의 산업밀도를 도출하여 4개의 실험집단으로 분류하여 비재무적 지표변수를 보완하였다. 인공신경망은 다층퍼셉트론(multi-layer perceptrons)과 역방향 학습(back-propagation )알고리듬으로 입력변수와 출력변수, 그리고 하나의 은닉층을 가지는 3층 퍼셉트론(three layer perceptron)을 사용하였으며 은닉충의 노드(node)수는 3개를 사용하였다. 입력변수로 안정성, 활동성, 수익성, 성장성을 나타내는 재무적 지표변수와 조직규모, 조직연령, 그 조직이 속한 산업의 밀도를 비재무적 지표변수로 산정하여 로지스틱회귀 분석과 인공신경망 기법으로 검증하였다. 로지스틱회귀분석 결과에서는 재무적 지표변수 모형의 전체적 예측적중률이 87.50%인 반면에 재무/비재무적 지표모형은 90.18%로서 비재무적 지표변수 사용에 대한 개선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적 중률을 나타내었다.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 1999.03a
• /
• pp.415-421
• /
• 1999

Altman의 연구(1965, 1977)나 Beaver의 연구(1986)와 같은 전통적 예측모형은 분석자의 판단에 따른 예측도가 높은 재무비율을 선정하여 다변량판별분석(MDA:multiple discriminant analysis), 로지스틱회귀분석 등과 같은 통계기법을 주로 이용해 왔으나 1980년 후반부터 인공지능 기법인 귀납적 학습방법, 인공신경망모형, 유전모형 등이 부실기업예측에 응용되기 시작했다. 최근 연구에서는 인공신경망을 활용한 변수 및 모형개발에 관한 보고가 있다. 그러나 지금까지의 연구가 주로 기업의 재무적 비율지표를 고려한 모형에 치중되었으며 정성적 자료인 비재무지표에 대한 검증과 선정이 자의적으로 이루어져온 경향이었다. 또한 너무 많은 입력변수를 사용할 경우 다중공선성 문제를 유발시킬 위험을 내포하고 있다. 본 연구에서는 부실기업예측모형을 수립하기 위하여 정량적 요인인 재무적 지표변수와 정성적 요인인 비재무적 지표변수를 모두 고려하였다. 재무적 지표변수는 상관분석 및 요인분석들을 통하여 유의한 변수들을 도출하였으며 비재무적 지표변수는 조직생태학내에서의 조직군내 조직사멸과 관련된 생태적 과정에 대한 요인들 중 조직군 내적요인으로 조직의 연령, 조직의 규모, 조직의 산업밀도를 도출하여 4개의 실험집단으로 분류하여 비재무적 지표변수를 보완하였다. 인공신경망은 다층퍼셉트론(multi-layer perceptrons)과 역방향 학습(back-propagation)알고리듬으로 입력변수와 출력변수, 그리고 하나의 은닉층을 가지는 3층 퍼셉트론(three layer perceptron)을 사용하였으며 은닉층의 노드(node)수는 3개를 사용하였다. 입력변수로 안정성, 활동성, 수익성, 성장성을 나타내는 재무적 지표변수와 조직규모, 조직연령, 그 조직이 속한 산업의 밀도를 비재무적 지표변수로 산정하여 로지스틱회귀 분석과 인공신경망 기법으로 검증하였다. 로지스틱회귀분석 결과에서는 재무적 지표변수 모형의 전체적 예측적중률이 87.50%인 반면에 재무/비재무적 지표모형은 90.18%로서 비재무적 지표변수 사용에 대한 개선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.

• Journal of the Korea Convergence Society
• /
• v.13 no.2
• /
• pp.85-91
• /
• 2022

As emphasized in the COVID-19 quarantine guidelines, hand washing is the most important prevention rule in tandem with distancing and mask. This study aimed to confirm relevant factors that affect practice of hand washing to find out approach for improvement of hand washing practice rate after COVID-19. Using the 2020 Community Health Survey data. As methods of research, this study searched for relevance by carrying out univariate logistic regression analysis, and also conducted multivariate logistic regression analysis using significant variables. Analysis results show that hand washing practice rate was high in females, well-educated, low age, cities, office job, the more people wear a face mask indoors, the higher the cycle of ventilation, the higher the cycle of disinfection and the more people maintain healthy distance. This study understood factors related to the rate of hand washing practice and results can be used as basic data for COVID-19 quarantine guidelines.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.8
• /
• pp.4881-4894
• /
• 2014

This study selected 83 manufacturing firms that had been delisted from the KOSDAQ market from 2009 to 2012 and the sample firms for the two-paired sampling method were compared with 83 normal firms running businesses with same items or in same industry. The 75 financial ratios for five years immediately before delisting were used for Mean Difference Analysis with those of normal firms. Fifteen variables assumed to be significant variables for five consecutive years out of the analysis were used to in the Dichotomous Classification Technique, Logistic Regression Analysis and Discriminant Analysis. As a result of those three analyses, the Logistic Regression Analysis model was found to show the greatest discrimination. This study is differentiated from previous studies as it assumed that the firm's failure proceeded slowly over long period of time and it tried to predict the firm's failure earlier using the five years' historical data immediately before failure, whereas previous studies predicted it using three years' data only. This study is also differentiated from the proceeding comparative studies by its statistically complex Multi-Variate Analysis and Dichotomous Classification Analysis, which general stakeholders can easily approach.

• Journal of Korea Society of Industrial Information Systems
• /
• v.14 no.5
• /
• pp.281-288
• /
• 2009

The purpose of this paper is to provide the statistical models for landslide prediction through quantification and AHP methods. Quantification method is a statistical method of providing quantity to qualitative variables by analyzing the observed data. In this paper, we suggest the quantification process based on the results of cannonical correlation analysis. In contrast with the quantification method which is based on given data the AHP(Analytic Hierarchy Process) technique is a kind of method based on questionaire data which is usually taken from professionals. We analyze both the real data(provided from KIGAM) and questionaire data collected from professionals of various related area. We developed two kinds of evaluation table which provide the scores of land slide possibility and the logistic model providing the probability of occurring landslide. Finally we compare the performance and evaluate the stability of the suggested two models.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.25 no.1
• /
• pp.21-28
• /
• 2021

Purpose Brown fat, or brown adipose tissue (BAT), is involved in non-shivering thermogenesis and creates heat through glucose metabolism. BAT activation occurs stochastically by internal factors such as age, sex, and body mass index (BMI) and external factors such as temperature and environment. In this study, as a retrospective, electronic medical record (EMR) observation study, statistical analysis is conducted to confirm BAT activation and various factors. Materials and Methods From January 2018 to December 2019, EMR of patients who underwent PET/CT scan at the National Cancer Center for two years were collected, a total of 9155 patients were extracted, and 13442 case data including duplicate scan were targeted. After performing a univariable logistic regression analysis to determine whether BAT activation is affected by the environment (outdoor temperature) and the patient's condition (BMI, cancer type, sex, and age), A multivariable regression model that affects BAT activation was finally analyzed by selecting univariable factors with P<0.1. Results BAT activation occurred in 93 cases (0.7%). According to the results of univariable logistic regression analysis, the likelihood of BAT activation was increased in patients under 50 years old (P<0.001), in females (P<0.001), in lower outdoor temperature below 14.5℃ (P<0.001), in lower BMI (P<0.001) and in patients who had a injection before 12:30 PM (P<0.001). It decreased in higher BMI (P<0.001) and in patients diagnosed with lung cancer (P<0.05) In multivariable results, BAT activation was significantly increased in patients under 50 years (P<0.001), in females (P<0.001) and in lower outdoor temperature below 14.5℃ (P<0.001). It was significantly decreased in higher BMI (P<0.05). Conclusion A retrospective study of factors affecting BAT activation in patients who underwent PET/CT scan for 2 years at the National Cancer Center was conducted. The results confirmed that BAT was significantly activated in normal-weight women under 50 years old who underwent PET/CT scan in weather with an outdoor temperature of less than 14.5℃. Based on this result, the patient applied to the factor can be identified in advance, and it is thought that it will help to reduce BAT activation through several studies in the future.

• 한국경영정보학회:학술대회논문집
• /
• 2007.06a
• /
• pp.619-624
• /
• 2007

본 연구는 유전 알고리듬에 기반한 새로운 도산예측기법을 개발하고 그 기법의 타당성 및 예측 우수성을 검증하는데 목적이 있다. 본 연구에서 제안하는 이진분류기법은 도산기업과 비도산기업을 대표할 수 있는 가상기업(virtual company)을 설정하고, 그 가상기업과 분류대상 기업 간의 유사도를 측정하여 도산여부를 분류하는 방법론으로, 가상기업의 변수 값과 각 변수의 가중치는 훈련용 자료의 분류정확도를 극대화할 수 있도록 유전 알고리듬을 이용하여 구하게 된다. 본 연구에서 제안하는 기법의 타당성을 검증하기 위해 기존의 도산예측기법과 예측성과를 실험을 통해 비교한 결과, 본 연구에서 개발한 기법의 예측력이 기존의 다변량판별분석, 로지스틱 회귀모형, 의사결정나무, 인공신경망 모형보다 높은 수준을 보이는 것을 확인하였다.

• The Journal of the Korea Contents Association
• /
• v.19 no.11
• /
• pp.22-32
• /
• 2019

The purpose of this study was to derive association between company's fringe benefits and retirement planning. The study analyzed the 2016 Korean Longitudinal Study of Ageing(KLoSA) and a total of 1,740 participants was included. To analyze the relationship between the number of the company's employee fringe benefit and the retirement planning, multiple logistic regression was conducted. As a result, we found multiple variables affecting the retirement planning including not only the number of the fringe benefits, but also the age, marital status, residence, private health insurance status, and subjective health status. Successful retirement planning for wage workers benefits not only the individuals or government, but companies also gain benefits such as improved productivity of workers and a better corporate image, so further research is needed on the effective implementation of the system, and the role of government to support this.

• Journal of the Korea Convergence Society
• /
• v.2 no.1
• /
• pp.21-29
• /
• 2011

The purpose of this study was to investigate the prevalence of depression and related to the factors among the rural people. The questionnaire survey using the Center for Epidemiology Studies-Depression Scale(CES-D) was conducted in the rural people. The subjects were 226 individuals, living in the rural area. The results of this study were as follows. In this study, the prevalence of depression was 15.0% in all and 18.3% in the elderly. The prevalence rate was higher in non educational, widowhood, higher income group. The prevalence rate was lower in the group of having good health status, having no chronic disease, low stress level. In the multiple logistic regression analysis, significant predictors of the depression were stress level whereas there was no relation with other factors. Based on the above findings, this study suggests that these risk factors of depression should be taken into consideration for the comprehensive mental health programs for the people living in the rural area.

• The Journal of the Korea Contents Association
• /
• v.22 no.6
• /
• pp.530-540
• /
• 2022

The aim of this study was to analyze the impacts of perceived economic instability on drinking frequency in the mist of exercising the strong social distancing in the early phase of COVID19 pandemic. The data were collected from 1,117 adults aged between 19 and 70 across the nation from May 13 to May 19 in 2020 by Embrain, an on-line research company. We used only 820(73.4%) out of 1,117 who answered that they had a drinking in 2020. Bi-variate analysis and multivariate multinomial logistic regression were performed using STATA16. Multinomial logistic regression results showed that the increase of employment instability was related to the increase of drinking frequency, whereas the increase of income instability was related to the decrease of drinking frequency. In sum, the impact of perceived economic instability during the early phase of pandemic may be presented as an increase or decrease of drinking frequency depending on the effect of employment instability and income instability.