• Title/Summary/Keyword: logistic information system

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Using Classification function to integrate Discriminant Analysis, Logistic Regression and Backpropagation Neural Networks for Interest Rates Forecasting

  • Oh, Kyong-Joo;Ingoo Han
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2000.11a
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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.

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The Information Distortion, Overstock and Stock-out Caused by the Budgetary Process in the Logistic Support (군수지원체계에서 예산과정에 의해 발생하는 정보왜곡과 초과재고 및 재고부족 분석)

  • Lim, Junoh;Park, Chong Goo
    • Journal of the Korea Society for Simulation
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    • v.25 no.4
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    • pp.65-75
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    • 2016
  • Unused spare parts of military equipments which have been kept in the warehouse for a long term have been recognized as wasting of defense budget which also decreased people's confidence in the field of national defence. It is known that overstock is caused by information distortion and bullwhip effect from downstream to upstream in the logistic support as is like business cases. After upgrading the logistic information system, it is possible for Army Logistics Command(ALC) to know demand information of end-user which is the key factor to reduce bullwhip effect. However, inventory is still overstocked and stock-out at the same time. Previous studies have not accounted for these phenomenons and have mainly focused on forecasting inventory level instead of budgetary process(budget period, PROLT, ASL/N-ASL). Thus, this study focuses on the information distortion, overstock and stock-out which caused by budgetary process in the logistic support with system dynamics and simulation.

A Study on RFID System Design and Expanded EPCIS Model for Manufacturing Systems (제조 시스템의 RFID System 설계 및 EPCIS 확장모형 연구)

  • Choi, Weon-Yong;Lee, Jong-Tae
    • Journal of the Korea Safety Management & Science
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    • v.9 no.6
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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.

APPLICATION OF LOGISTIC REGRESSION MODEL AND ITS VALIDATION FOR LANDSLIDE SUSCEPTIBILITY MAPPING USING GIS AND REMOTE SENSING DATA AT PENANG, MALAYSIA

  • LEE SARO
    • Proceedings of the KSRS Conference
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    • 2004.10a
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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.

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Fuzzy c-Logistic Regression Model in the Presence of Noise Cluster

  • Alanzado, Arnold C.;Miyamoto, Sadaaki
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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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.

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A Study on the Fitness of Korea's Hub-Port Strategy in Northeast Asia by SCM (공급사슬관리에 의한 동북아 거점항만전략의 적합성에 관한 연구)

  • Lee In-Soo;Ahn Ki-Myung;Kim Hyun-Duk
    • Journal of Navigation and Port Research
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    • v.29 no.8 s.104
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    • pp.709-714
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    • 2005
  • The purpose of this research is to verify the strategic fitness and relevance of the hub port strategy by SCM in Northeast Asia and to find a method to be a hub-port with a competitive edge. The fitness of the hub port development strategy is analysed by the structural equation model. The essential results of the research show that minimizing lead time from arrival of ship to inland transport and maximizing logistic services of each stage are important to provide optimal logistic service. And value-added port supply chain strategy is highly co-related with all the parts of port operation system, port transport system, distribution park and port information system. It shows that: various value added logistic service activity is more important than lowing cost; inland multimodal system should be rightly connected; distribution park should be connected to industry park to be a port cluster; and port information system should be developed.

Logistic Regression for Investigating Credit Card Default

  • Yang, Jeong-Won;Ha, Sung-Ho;Min, Ji-Hong
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 2008.10b
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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%.

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A Study on the Competition of Railroad Logistics for the Openness of Railroad Industry: Focused on Distribution and Logistic Information System (철도 산업 개방에 대비한 철도물류의 경쟁력 제고 방안 연구 -유통 및 물류 정보화 중심으로-)

  • Lee Soon Cheul;Yoo Jae-Kyun
    • Proceedings of the KSR Conference
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    • 2003.05a
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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.

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Conceptual Data Modeling of Integrated Information System for Research & Development Configuration Management (연구개발 형상관리 자동화체계에 대한 개념적 데이터모델링)

  • 김인주
    • Journal of the military operations research society of Korea
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    • v.25 no.1
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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.

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APPLICATION OF LOGISTIC REGRESS10N A MODEL FOR LANDSLIDE SUSCEPTIBILITY MAPPING USING GIS AT JANGHUNG, KOREA

  • Saro, Lee;Choi, Jae-Won;Yu, Young-Tae
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.04a
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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.

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