• Title/Summary/Keyword: Logistic System

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Strategies for Technological Standardization of National Logistics (국가물류표준화 기술체계에 따른 추진 전략)

  • Moon, Dae-Seop;Lee, Soon-Cheul
    • Proceedings of the KSR Conference
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    • 2003.10b
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    • pp.354-359
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    • 2003
  • The purpose of this study is to establish the technical system of national logistics standardization and to strengthen the national competitiveness through reduction of the logistic cost We review of the government and private roles in the logistic sectors and suggest plans for the improvement of logistics standardization for its completion in the unit load system in Korea. We conclude that a symmetrical logistics standardization may accomplish to reduce the costs of national logistics.

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Development of Discriminant Analysis System by Graphical User Interface of Visual Basic

  • Lee, Yong-Kyun;Shin, Young-Jae;Cha, Kyung-Joon
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.2
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    • pp.447-456
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    • 2007
  • Recently, the multivariate statistical analysis has been used to analyze meaningful information for various data. In this paper, we develope the multivariate statistical analysis system combined with Fisher discriminant analysis, logistic regression, neural network, and decision tree using visual basic 6.0.

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Innovative Mechanisms in the Procurement Logistics of Kazakhstan

  • Zhatkanbaev, Erzhan B.;Mukhtar, Ernur S.;Suyunchaliyeva, Maiya M.
    • The Journal of Asian Finance, Economics and Business
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    • v.2 no.3
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    • pp.33-36
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    • 2015
  • Innovations in the procurement logistics now is very popular in Kazakhstan. Nowadays there are a lot of documents of transport infrastructure and Kazakhstan logistic system is developing more and more. Procurement logistic is the direction where you can count, sometimes you can buy some products or transport equipments. Logistic in Kazakhstan is new direction, there are a lot of young people who choose this specialty and will stay demanded. Our president said a lot of words in strategies about development in logistics and so there will be new methods that will be used here. Innovations are new technologies that are used in different spheres so this structure as procurement logistic will develop in Kazakhstan and every citizen of our republic will support it. Transport systems are used for transitions different products so there are a lot new transition roads for example Western China - Western Europe; Astana-Almaty; Astana-Ust-Kamenogorsk; Astana-Aktobe, Atyrau; Almaty - Ust-Kamenogorsk; Karaganda - Zhezkazgan - Kyzylorda; Atyrau-Astrakhan, it helps Kazakhstan to support international links between other countries.

Data Mining for Knowledge Management in a Health Insurance Domain

  • Chae, Young-Moon;Ho, Seung-Hee;Cho, Kyoung-Won;Lee, Dong-Ha;Ji, Sun-Ha
    • Journal of Intelligence and Information Systems
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    • v.6 no.1
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    • pp.73-82
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    • 2000
  • This study examined the characteristicso f the knowledge discovery and data mining algorithms to demonstrate how they can be used to predict health outcomes and provide policy information for hypertension management using the Korea Medical Insurance Corporation database. Specifically this study validated the predictive power of data mining algorithms by comparing the performance of logistic regression and two decision tree algorithms CHAID (Chi-squared Automatic Interaction Detection) and C5.0 (a variant of C4.5) since logistic regression has assumed a major position in the healthcare field as a method for predicting or classifying health outcomes based on the specific characteristics of each individual case. This comparison was performed using the test set of 4,588 beneficiaries and the training set of 13,689 beneficiaries that were used to develop the models. On the contrary to the previous study CHAID algorithm performed better than logistic regression in predicting hypertension but C5.0 had the lowest predictive power. In addition CHAID algorithm and association rule also provided the segment characteristics for the risk factors that may be used in developing hypertension management programs. This showed that data mining approach can be a useful analytic tool for predicting and classifying health outcomes data.

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Development of EDI Model in the Port-Logistics Industries (항만물류산업에서 EDI 활성화 모형개발)

  • Shin Chang-Hoon;Kim Yul-Seong
    • Journal of Navigation and Port Research
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    • v.29 no.10 s.106
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    • pp.907-913
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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 activated yet because of problems of documentation duplication and system connectivity and so on. The purpose of this research is to make a model which can activate the system of port-logistic information. In addition, We suggest a definite and feasible model by group and types of port-logistic industry.

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.

A PRODUCTION METHOD OF LANDSLIDE HAZARD MAP BY COMBINING LOGISTIC REGRESSION ANALYSIS AND AHP (ANALYTICAL HIERARCHY PROCESS) APPROACH

  • Lee, Yong-Jun;Park, Geun-Ae;Kim, Seong-Joon
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.547-550
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    • 2006
  • This study is to suggest a methodology to produce landslide hazard map by combining LRA (Logistic Regression Analysis) and AHP (Analytic Hierarchy Program) Approach. Topographic factors (slope, aspect, elevation), soil drain, soil depth and land use were adopted to classify landslide hazard areas. The method was applied to a 520 $km^2$ region located in the middle of South Korea which have occurred 39 landslides during 1999 and 2003. The suggested method showed 58.9 % matching rate for the real landslide sites comparing with the classified areas of high-risk landslide while LRA and AHP showed 46.1 % and 48.7 % matching rates respectively.

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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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A Study on general logistic center of agriculture products for location selection model (농산물 종합물류센터조성을 위한 입지선정 평가요인 분석)

  • 김규창
    • Journal of Distribution Research
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    • v.3 no.1
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    • pp.145-158
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    • 1998
  • The selection of proposed sites for the general logistic center of agriculture products would be made the most suitable place by considering the spread of population as real consumers, the prospect of the demand, the expansion of traffic system, the regional, hourly and carring traffic volume and the use of land based urban planning, etc. As the preconsideration, the possible occupant companies have to be selected on the category of business and the district. After posing questions and having interview, several selected regions would be compared and analysed for deciding the most suitable place. The model for the general logistic center of agricultural products must be selected taking key factors approach for choosing key factors at first and referring to many documentary records. And the more, cooperating with the specialists for location selection and making objective questions to concerned companies, the most suitable place is selected by marking high score for the moderate land cost, the low traffic jam, the connection with the back cities and the possible expansion as the general logistic center of agriculture products.

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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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