• Communications for Statistical Applications and Methods
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• 제15권4호
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• pp.615-631
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• 2008

재무자료에 대한 신용평가모형은 각각의 재무변수를 평활한 예측부도율로 변환하여 사용한다. 본 연구에서는 연속형 재무자료를 변환하여 설정된 신용평가모형의 문제점을 살펴보고, 연속형 재무변수를 다양한 형태로 범주화한 신용평가모형들을 제안한다. 범주형 재무자료를 사용해서 개발한 여러 종류의 신용평가모형들의 성과를 다양한 적합성 검증 방법으로 비교하고, 범주형 재무자료를 이용한 신용평가모형의 유용성을 토론한다.

• 자원환경지질
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• 제38권1호
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• pp.45-55
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• 2005

산사태 취약성 분석을 위해 적용된 기존 GIS 기반 확률론적 공간 통합 모델은 범주형과 연속형 자료와 같이 서로 다른 형태의 자료의 처리를 위한 이론적 배경과 효율적인 방법론을 제시하지 못하였다. 이 논문에서는 우도비의 틀 안에서 연속형 자료를 직접적으로 사용할 수 있도록 비모수적 경험적 추정 모델과 모수적 예측적 판별 분석 모델을 적용하였다. 그리고 유사율과 예측비율곡선을 계산함으로써 두 모델을 정량적으로 비교하고자 하였다. 제안 모델을 비 교하기 위해 1998년 여름 산사태로 많은 피해를 입은 장흥 지역과 보은 지역을 대상으로 사례연구를 수행하였다. 장 흥 지역에서는 두 모델이 유사한 예측 능력을 나타내었으나, 보은 지역에서는 모수적 예측적 판별 분석 모델이 보다 높은 예측 능력을 나타내었다. 결론적으로 제안한 두 모델은 산사태 취약성 분석을 위한 연속형 자료 표현에 효율적 으로 적용될 수 있으며, 두 모델이 개별적인 연속형 자료 표현의 특성을 가지고 있기 때문에 다른 사례 연구를 통한 검증 작업이 병행되어야 할 것으로 생각된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.622-625
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• 2004

This paper presents multi-source spatial data integration models based on probability theory for landslide hazard assessment. Four probabilistic models such as empirical likelihood ratio estimation, logistic regression, generalized additive and predictive discriminant models are proposed and applied. The models proposed here are theoretically based on statistical relationships between landslide occurrences and input spatial data sets. Those models especially have the advantage of direct use of continuous data without any information loss. A case study from the Gangneung area, Korea was carried out to quantitatively assess those four models and to discuss operational issues.

• 한국소음진동공학회논문집
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• 제21권2호
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• pp.146-153
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• 2011

Model based machine condition diagnosis methods are generally using a normal and many failure models which need sufficient data to train the models. However, data, especially for failure modes of interest, is very hard to get in real applications. So their industrial applications are either severely limited or impossible when the failure models cannot be trained. In this paper, continuous hidden Markov model(CHMM) with only a normal model has been suggested as a very promising machine condition diagnosis method which can be easily used for industrial applications. Generally hidden Markov model also uses many pattern models to recognize specific patterns and the recognition results of CHMM show the likelihood trend of models. By observing this likelihood trend of a normal model, it is possible to detect failures. This method has been successively applied to arc weld defect diagnosis. The result shows CHMM's big potential as a machine condition monitoring method.

• 산업경영시스템학회지
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• 제17권31호
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• pp.73-80
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• 1994

Sequentiality in decision making is an inherent characteristic of the R&D Process, Conceptual changes are noted during the Course of the Project which represent a continuous improvement in the quality of the data available during the various project stages. In this paper, Eight characteristic types of project evaluation models have been developed economic index models, portfolio models, decision theory models, risk analysis models, frontier models, scoring models, profile models and checklists. Each of these will be critically reviewed and appraised.

• 한국막학회:학술대회논문집
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• 한국막학회 1993년도 춘계 총회 및 학술발표회
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• pp.52-53
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• 1993

The pervaporation behavior of EtOH/Water mixture through IPN membranes was predicted in this study. The pervaporation characteristics of single polymer membrane were modeled according to the "six-coefficients model" proposed by Brun. In the case of the IPN membrane, two models were proposed according to the phase structure of the IPN. For a uniphase membrane with no phase separation, the compositional average of the single polymer membrane was used. in the case of the phase separated IPN's two cases existed. The first was the island and sea model: in which one phase was continuous and the other was dispersed. The second was the co-continuous model where two continuous phases existed. For these cases, the permeation rate and the separation factor of the IPN membrane were calculated using the experimental sorption data and the cornponent polymer properties. Comparison with the experimental data indicated that these models could be used to predict the performances of IPN membranes depending on the morphology of the IPN.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.145-149
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• 1997

This paper describes a methodology for the development of models of discrete event system. The methodology is based on transformation of continuous state space into discrete one to homomorphically represent dynamics of continuous processes in discrete events. This paper proposes a formal structure which can coupled discrete event system models within a framework. The structure employs the discrete event specification formalism for the discrete event system models. The proposed formal structure has been applied to develop a discrete event specification model for the complex spectral density analysis of strip for urin analyzer system. For this, spectral density data of strip is partitioned into a set of Phases based on events identified through urine spectrophotometry. For each phase, a continuous system of the continuous model for the urine spectral density analysis has been simulated by programmed C++. To validate this model, first develop the discrets event specification model, then simulate the model in the DEVSIM++ environment. It has the similar simulation results for the data obtained from the continuous system simulation. The comparison shows that the discrete event specification model represents dynamics of the urine spectral density at each phase.

• 한국IT서비스학회지
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• 제10권3호
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• pp.113-126
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• 2011

The smelting and the continuous casting of steel are important processes that determine the quality of steel products. Especially most of quality defects occur during solidification of the steel continuous casting process. Although quality control techniques such as six sigma, SQC, and TQM can be applied to the continuous casting process for improving quality of steel products, these techniques don't provide real-time analysis to identify the causes of defect occurrence. To solve problems, we have developed a detection model using decision tree which identified abnormal transactions to have a coarse grain structure. And we have compared the proposed model with models using neural network and logistic regression. Experiments on steel data showed that the performance of the proposed model was higher than those of neural network model and logistic regression model. Thus, we expect that the suggested model will be helpful to control the quality of steel products in real-time in the continuous casting process.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.456-457
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• 2021

최근, 실내 위치 기반 서비스를 보다 정확하게 제공하기 위해서 Wi-Fi 핑거프린트와 딥러닝을 이용한 기술이 연구되고 있다. 딥러닝 모델 중에서 과거의 정보를 기억할 수 있는 RNN 모델은 실내측위에서 연속된 움직임을 기억할 수 있어 측위 오차를 줄일 수 있다. 실내 측위에서 RNN 모델을 사용하는 경우 수집된 학습 데이터가 연속적인 순차 데이터이어야 한다. 그러나 특정 위치 정보를 판단하기 위해 수집된 Wi-Fi 핑거프린트 데이터는 특정 위치에 대한 RSSI만 기록되었기 때문에 RNN 모델의 학습 데이터로 사용이 불가능하다. 본 논문은 Wi-Fi 핑거프린트 데이터를 기반으로 RNN 모델의 순차적인 입력 데이터의 생성을 위한 영역 클러스터링 방법에 대해 제안한다.

• Communications for Statistical Applications and Methods
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• 제10권1호
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• pp.239-246
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• 2003

Statisticians, or data miners, are often requested to assess the importances of input variables in the given supervised learning model. For the purpose, one may rely on separate ad hoc measures depending on modeling types, such as linear regressions, the neural networks or trees. Consequently, the conceptual consistency in input variable importance measures is lacking, so that the measures cannot be directly used in comparing different types of models, which is often done in data mining processes, In this short communication, we propose a unified approach to the importance measurement of input variables. Our method uses sensitivity analysis which begins by perturbing the values of input variables and monitors the output change. Research scope is limited to the models for continuous output, although it is not difficult to extend the method to supervised learning models for categorical outcomes.