• Journal of Korean Academy of Nursing
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• v.43 no.2
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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.

• Proceedings of the KIEE Conference
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• 1995.07b
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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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• v.11 no.3
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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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.2
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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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.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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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.

• The monthly packaging world
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• s.115
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• pp.146-151
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• 2002

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.369-375
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• 2005

The rapid growth of economy in china leads to concentrate throughput volume of World to North East Asia. Ports in North East Asia have to cope with rapid changes in environments. In order for a port to compete in the global market, it must provide proper productivity and promptly services of port. The system of information hold a key in port-logistic industries. Most ports make every effort to set up and operate the system of Information. Busan port already set up the system of port-logistic information such as Port-Mis, KROIS. But it is not activate yet because of problems of security and certification and so on. The purpose of this paper is to make Model which can activate the system of port-logistic information. In addition to, We suggest definite and feasible model by group and types of port-logistic industry.

• The Journal of Engineering Geology
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• v.31 no.1
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• pp.31-42
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• 2021

Database of Cut-slope management system (CSMS) has been constructed based on investigations of all slopes on the roads of the whole country. The investigation data is documented by human, so it is inevitable to avoid human-error such as missing-data and incorrect entering data into computer. The goal of this paper is constructing a prediction model based on several machine-learning algorithms to solve those imperfection problems of the CSMS data. First of all, the character-type data in CSMS data must be transformed to numeric data. After then, two algorithms, i.g., multinomial logistic regression and deep-neural-network (DNN), are performed, and those prediction models from two algorithms are compared. Finally, it is identified that the accuracy of DNN-model is better than logistic model, and the DNN-model will be utilized to improve data-quality.

• Journal of The Geomorphological Association of Korea
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• v.24 no.2
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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.