• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
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• pp.417-426
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• 2000

This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.

• 한국시뮬레이션학회논문지
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• 제25권4호
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• pp.65-75
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• 2016

장기간 사용하지 않는 군수 수리부속품으로 인한 국방예산의 낭비가 발생하는 반면에 야전부대에서 재고부족으로 필요한 수리부속이 적시에 보급되지 못해 문제가 되고 있다. 초과재고의 발생 원인은 민간분야처럼 다단계 군수지원체계에서 하위공급망에서 상위공급망으로 갈수록 수요정보왜곡에 의한 채찍효과 때문인 것으로 알려져 있다. 하지만 군수정보체계 개선 이후 채찍효과의 가장 직접적인 원인이었던 사용자부대의 수요정보를 군수사가 공유할 수 있음에도 불구하고 초과재고 현상이 지속적으로 발생하고 있고 기존의 연구만으로 재고부족 현상은 설명할 수 없다. 또한 기존의 연구는 주로 적정 재고량을 예측하는데 중점을 두었으며 예산과정의 특성(예산주기, 조달기간, 인가저장 유무)은 크게 관심을 두지 않았다. 따라서 본 연구의 목적은 시스템 다이내믹스 이론과 시뮬레이션 기법을 통해 군수지원체계에서 예산과정에 의해 발생하는 정보왜곡과 이로 인한 초과재고 및 재고부족 현상을 분석하는 것이다.

• 대한안전경영과학회지
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• 제9권6호
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• pp.123-135
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• 2007

In the recent years, the companies have manually recorded a production status in a work diary or have mainly used a bar code in order to collect each process's progress status, production performance and quality information in the production and logistics process in real time. But, it requires an additional work because the worker's record must be daily checked or the worker must read it with the bar code scanner. At this time, data's accuracy is decreased owing to the worker's intention or mistake, and it causes the problem of the system's reliability. Accordingly, in order to solve such problem, the companies have introduced RFID which comes into the spotlight in the latest automatic identification field. In order to introduce the RFID technology, the process flow must be analyzed, but the ASME sign used by most manufacturing companies has the difficult problem when the aggregation event occurs. Hence, in this study, the RFID logistic flow analysis Modeling Notation was proposed as the signature which can analyze the manufacturing logistic flow amicably, and the manufacturing logistic flow by industry type was analyzed by using the proposed RFID logistic flow analysis signature. Also, to monitor real-time information through EPCglobal network, EPCISEvent template by industry was proposed, and it was utilized as the benchmarking case of companies for RFID introduction. This study suggested to ensure the decision-making on real-time information through EPCglobal network. This study is intended to suggest the Modeling Notation suitable for RFID characteristics, and the study is intended to establish the business step and to present the vocabulary.

• 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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.431-434
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• 2003

In this paper we introduce a modified objective function for fuzzy c-means clustering with logistic regression model in the presence of noise cluster. The logistic regression model is commonly used to describe the effect of one or several explanatory variables on a binary response variable. In real application there is very often no sharp boundary between clusters so that fuzzy clustering is often better suited for the data.

• 한국항해항만학회지
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• 제29권8호
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• pp.709-714
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• 2005

본 논문의 목적은 우리 항만이 동북아 거점항만으로 변신하는데 필요한 항만공급사슬전략을 도출하여 거점항만으로의 발전전략의 적합성을 분석하였다. 경쟁항만의 발전 잠재력을 충분히 고려하고 우리 항만의 시설${\cdot}$서비스수준의 미흡성을 하루속히 보완하는 유연한 항만 공급능력의 확보, 항만리드타임(접안시간, 양하역시간 등)의 최소화와 뭍류서비스를 극대화${\cdot}$다양화할 수 있는 모듈방식의 항만운영의 다양화가 필요함을 검증하였다. 특히, 거점항만 개발전략에서 다양한 부가서비스의 제공과 실질적인 부가가치를 창출할 수 있는 방향으로 항만배후부지 개발이 매우 중요한 것으로 나타나고 있다.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2008년도 추계 공동 국제학술대회
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• pp.164-169
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• 2008

The increasing late-payment rate of credit card customers caused by a recent economic downturn are incurring not only reduced profit of department stores but also significant loss. Under this pressure, the objective of credit forecasting is extended from presumption of good or bad customers to contribution to revenue growth. As a method of managing defaults of department store credit card, this study classifies credit delinquents into some clusters, analyzes repaying patterns of customers in each cluster, and develops credit forecasting system to manage delinquents of department store credit card using data of Korean D department store's delinquents. The model presented by this study uses Kohonen network, a kind of artificial neural network of data mining techniques to cluster credit delinquents into groups. Logistic regression model is also used to predict repayment rate of customers of each cluster per period. The accuracy of presented system for the whole clusters is 92.3%.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2003년도 춘계학술대회 논문집
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• pp.121-125
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• 2003

This study discusses how the appropriate distribution and logistic information system of the railroad industry will be developed when the Korean railroad will be open toward northeast Asia area through South Korea and China/Russia in the rail-ferry project and/or the inter-Korean railroad connection project in the fnture. This study suggests that the Korea railroad industry should build the own efficient information system of railroad distribution and logistics in the notheast Asia area far both the extension of customer services and the competition with peripheral countries around the pacific.

• 한국국방경영분석학회지
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• 제25권1호
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• pp.87-106
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• 1999

There are many technical datum in related with design, test & evaluation and logistic support which will be exchanged between geographically isolated units and heterogeneous hardwares & softwares in developing and operating the weapon systems. The paper proposes the conceptual database schema to establish configuration management information systems in which these datum can be automatically interchanged, tracked, audited and status-accounted without errors under the various environments. The paper investigates how to identify and classify the data in accordance with document identification, task analysis, system development, logistic support, system test & evaluation and data management. Furthermore, the investigation includes drawing the subject areas and modeling the conceptual database schema to explain the relationships between these datum. Thus, the paper results in the conceptual framework and data models of configuration management information systems, while additional customization efforts be required in applying the models to a specific weapon systems R&D.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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• pp.64-64
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• 2003

The aim of this study is to apply and verify of logistic regression at Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite images, field surveys, and maps of the topography, soil type, forest cover, geology and land use were constructed to spatial database. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography were calculated from the topographic database.13${\times}$1ure, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter and density of forest were extracted from the forest database. Land use was classified from the Landsat TM image satellite image. As each factor's ratings, the logistic regression coefficient were overlaid for landslide susceptibility mapping. Then the landslide susceptibility map was verified and compared using the existing landslide location. The results can be used to reduce hazards associated with landslides management and to plan land use and construction.