• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.269-278
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• 2006

This paper presents the new hybrid data mining technique using error pattern, modeling of improving classification accuracy. The proposed method improves classification accuracy by combining two different supervised learning methods. The main algorithm generates error pattern modeling between the two supervised learning methods(ex: Neural Networks, Decision Tree, Logistic Regression and so on.) The Proposed modeling method has been applied to the simulation of 10,000 data sets generated by Normal and exponential random distribution. The simulation results show that the performance of proposed method is superior to the existing methods like Logistic regression and Discriminant analysis.

• 산업공학
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• 제17권3호
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• pp.249-260
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• 2004

The objective of this study is to measure and to predict the efficiency of participating groups of BK 21 by using DEA. DEA is a methodology to measure and to evaluate the relative efficiency of a homogeneous set of decision-making units (DMUs) in a process which uses multiple inputs to produce multiple outputs. In order to reflect the effect of the environmental factors of BK 21, we consider not only a general DEA model but also a logistic model for DEA. As a result, location of participating groups of BK 21 turns out to be significant. Our proposed approach can predict the efficiency of a new BK 21 group with given environmental factors. It is expected that these models can give a feedback for effective management of BK 21.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.1161-1164
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• 2005

In this paper, we proposed the technique to estimate the life cycle of Internet content services based on the logistic regression model. In this paper, to define parameters of Internet contents estimating life cycle by logistic regression model, we used market size, traffic amount, page view and session-visit number as the parameters of Internet contents estimating life cycle by logistic regression model. In this paper, to compare the performance of our proposed scheme, we estimated life cycle for the download services of bell sound & character contents in mobile network. As a result, using our proposed logistic regression, we were able to estimate exactly the life cycle of the download services of bell sound & character contents.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2006년도 춘계학술발표회 논문집
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• pp.339-344
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• 2006

Slope failures are happen to natural disastrous when they occur in mountainous areas adjoining highways in Korea. The accidents associated with slope failures have increased due to rapid urbanization of mountainous areas. Therefore, Regular maintenance is essential for all slope and conducted to maintain road safety as well as road function. In this study, we take priority of making a database of risk factor of the failure of a slope before assesment and analysis. The purpose of this paper is to recommend a standard of Slope Management Information Sheet(SMIS) like as Hazard Map. The next research, we suggest to pre-estimated model of a road slope using Logistic Regression Model.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.310-313
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• 2004

The aim of this study is to evaluate the hazard of landslides at Penang, Malaysia, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature and distance from drainage, all from the topographic database; lithology and distance from lineament, taken from the geologic database; land use from TM satellite images; and the vegetation index value from SPOT satellite images. Landslide hazardous area were analysed and mapped using the landslide-occurrence factors by logistic regression model. The results of the analysis were verified using the landslide location data and compared with probabilistic model. The validation results showed that the logistic regression model is better prediction accuracy than probabilistic model.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.977-989
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• 2011

The half logistic distribution has been used intensively in reliability and survival analysis especially when the data is censored. In this paper, we provide Bayesian estimation of the shape parameter and reliability function in the generalized half logistic distribution based on progressively Type-II censored data under various loss functions. We here consider conjugate prior and noninformative prior and corresponding posterior distributions are obtained. As an illustration, we examine the validity of our estimation using real data and simulated data.

• Journal of the Korean Data and Information Science Society
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• 제22권3호
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• pp.597-603
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• 2011

The half logistic distribution has been used intensively in reliability and survival analysis especially when the data is censored. In this paper, we provide prole likelihood estimation of the shape parameter and scale parameter in the generalized half logistic distribution based on progressively Type-II censored data. We also introduce approximate maximum prole likelihood estimates for the scale parameter. As an illustration, we examine the validity of our estimation using real data and simulated data.

• Journal of the Korean Data and Information Science Society
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• 제24권6호
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• pp.1455-1464
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• 2013

This paper develops maximum likelihood estimators (MLEs) of unknown parameters in an exponentiated half-logistic distribution based on a progressively type-II censored sample. We obtain approximate confidence intervals for the MLEs by using asymptotic variance and covariance matrices. Using importance sampling, we obtain Bayes estimators and corresponding credible intervals with the highest posterior density and Bayes predictive intervals for unknown parameters based on progressively type-II censored data from an exponentiated half logistic distribution. For illustration purposes, we examine the validity of the proposed estimation method by using real and simulated data.

• 한국국방경영분석학회지
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• 제34권2호
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• pp.43-61
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• 2008

성과기반군수는 전투준비태세를 향상시키고 무기체계의 수법주기비용을 절감하기 위하여 연구되었다. 최근 미국 국방부는 성과기반군수를 연구하고 발전시켜서 이것을 미국 군수분야에 적용하고 있다. 따라서 본 연구논문에서는 미국의 군수기원 분야의 발전동향을 살펴보고 우리나라의 군수지원 분야의 실태를 분석한 후, 효율적인 군수지원을 위하여 성과기반군수를 활용한 군수지원 발전방안을 제시하였다.

• 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.