• 대한간호학회지
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• 제43권2호
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• pp.154-164
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• 2013

Purpose: The purpose of this article is twofold: 1) introducing logistic regression (LR), a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, and 2) examining use and reporting of LR in the nursing literature. Methods: Text books on LR and research articles employing LR as main statistical analysis were reviewed. Twenty-three articles published between 2010 and 2011 in the Journal of Korean Academy of Nursing were analyzed for proper use and reporting of LR models. Results: Logistic regression from basic concepts such as odds, odds ratio, logit transformation and logistic curve, assumption, fitting, reporting and interpreting to cautions were presented. Substantial shortcomings were found in both use of LR and reporting of results. For many studies, sample size was not sufficiently large to call into question the accuracy of the regression model. Additionally, only one study reported validation analysis. Conclusion: Nursing researchers need to pay greater attention to guidelines concerning the use and reporting of LR models.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.913-915
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• 1995

In this paper, a transient signal classification system using logistic regression and neural networks is presented, where four neural networks such as MLP, MLP-Class, RBF and LVQ are utilized to classify given transient signals, based on the logistic regression method. Also, some test results with experimental transient signal data are provided.

• Communications for Statistical Applications and Methods
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• 제11권3호
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• pp.583-595
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• 2004

For the Korean Economically Active Population Survey(EAPS), we consider the composite estimator based on logistic regression model to estimate the unemployment rate for small areas(Si/Gun). Also, small area estimation technique based on hierarchical generalized linear model is proposed to include the random effect which reflect the characteristic of the small areas. The proposed estimation techniques are applied to real domestic data which is from the Korean EAPS of Choongbuk. The MSE of these estimators are estimated by Jackknife method, and the efficiencies of small area estimators are evaluated by the RRMSE. As a result, the composite estimator based on logistic model is much more efficient than others and it turns out that the composite estimator can produce the reliable estimates under the current EAPS system.

• 대한전기학회논문지:전력기술부문A
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• 제50권2호
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• pp.90-95
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• 2001

Electric arc furnaces (EAFs) has a process to cause the degradation of the electric power quality such as voltage flicker. In order to adequately understand and analyze the effects on the power system from these loads, obtaining an accurate representation of the characteristics of the loads is crucial. In this paper, a mixed chaotic EAF model to represent the low frequency and high frequency variations of the arc current respectively has been proposed. The Lorenz system may contribute to the low frequency components of arc current and the logistic equation may contribute to the high frequency components, and the proposed mixed model will be a combination of both Lorenz and logistic model. The concept of chaotic parameters, such as chaotic resistance, inductance of admittance has been also proposed for the characterization of arc furnace operation and the highly nonlinear physical processes. The power quality indices are calculated from the simulated waveforms and compared with the actual power quality indices statistics in order to illustrate the model's capabilities.

• 산업경영시스템학회지
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• 제46권4호
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• pp.133-141
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• 2023

Approximately 40,000 elevators are installed every year in Korea, and they are used as a convenient means of transportation in daily life. However, the continuous increase in elevators has a social problem of increased safety accidents behind the functional aspect of convenience. There is an emerging need to induce preemptive and active elevator safety management by elevator management entities by strengthening the management of poorly managed elevators. Therefore, this study examines domestic research cases related to the evaluation items of the elevator safety quality rating system conducted in previous studies, and develops a statistical model that can examine the effect of elevator maintenance quality as a result of the safety management of the elevator management entity. We review two types: odds ratio analysis and logistic regression analysis models.

• 월간포장계
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• 통권115호
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• pp.146-151
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• 2002

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2002년도 추계정기학술대회
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• pp.203-212
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• 2002

This study examined the predictive power of data mining algorithms by comparing the performance of logistic regression and decision tree algorithm, called CHAID (Chi-squared Automatic Interaction Detection), On the contrary to the previous studies, decision tree performed better than logistic regression. We have also developed a CDSS (Clinical Decision Support System) with three modules (doctor, nurse, and patient) based on data warehouse architecture. Data warehouse collects and integrates relevant information from various databases from hospital information system (HIS ). This system can help improve decision making capability of doctors and improve accessibility of educational material for patients.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2005년도 춘계학술대회 논문집
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• pp.369-375
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• 2005

중국 경제의 급성장으로 인한 전세계 물동량의 동북아시아로의 집중현상은 부산항을 포함한 지역 내 항만들의 경쟁을 점차 심각해지게 하고 있다. 이에 동북아시아 항만들은 생산성과 더불어 항만의 서비스를 극대화하고자 하는 노력을 기울이고 있으며 항만이 제공하여야 할 서비스 중 가장 중요하게 부각되고 있는 항만물류정보 시스템 구축 및 효율적 운영에 총력을 기울이고 있는 실정이다. 그러나 부산항이 경우, 이미 항만물류 정보시스템은 구축이 되어 있으나 보안 및 인증문제 등으로 인해 아직 활성화 되지 못하였다. 이에 본 연구에서는 부산항 항만물류산업에서 EDI의 활용도를 높이기 위한 전체적인 연구모형 도출과 항만물류업체를 업종별, 집단별로 구분하여 차별화된 활성화 모형을 도출하는 것을 목적으로 하고 있다.

• 지질공학
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• 제31권1호
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• pp.31-42
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• 2021

도로비탈면관리시스템(Cut-Slope Management System, CSMS)은 전국 일반국도 비탈면에 대해 기초·정밀 조사를 바탕으로 데이터베이스를 구축해왔다. 그런데 이러한 데이터는 사람에 의해 기록되기 때문에 데이터 누락 및 오기입 문제가 발생할 수밖에 없다. 본 연구에서는 데이터의 불완전성 문제를 극복하기 위해 여러 머신러닝 기반의 예측모델들을 개발하고 이를 이용한 데이터 품질 강화 가능성을 검토하고자 하였다. 우선 다 범주 문자형 데이터를 수치화하는 과정을 수행하였고, 선정된 데이터 항목들에 대해 다항 로지스틱 회귀분석(Multinomial Logistic Regression)과 심층신경망(Deep-Neural-Network) 기반의 예측모델들을 개발하였다. 그 결과, 심층신경망 모델들의 정확도가 월등히 높은 것으로 나타났다. 향후 개발된 모델들을 활용하여 누락 및 오기입 데이터의 보완이 가능할 것으로 기대된다.

• 한국지형학회지
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• 제24권2호
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• pp.91-101
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• 2017

Quantitative forecasting methods based on spatial data and geographic information system have been used in predicting the landslide location. This study compared the simulated results of logistic, Bayesian, and maximum entropy models to understand the uncertainties of each model and identify the main factors that influence landslide. The study area is Boeun gun where 388 landslides occurred in the year of 1998. The verification results showed that the AUC of the three models was 0.84. However, the landslide susceptibility distribution of Maxent model was different from those of the other two models. With the same landslide occurrence data, the result of high susceptible area in Maxent model is smaller than Logistic or Bayesian. Maxent model, however, proved to be more efficient in predicting landslide than the other two models. In Maxent's simulations, the responsible factors for landslide susceptibility are timber age class, land cover, timber diameter, crown closure, and soil drainage. The results suggest that it is necessary to consider the possibility of overestimation when using Logistic or Bayesian model, and forest management around the study area can be an effective way to minimize landslide possibility.