• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.175-180
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• 2011

Nowadays, the advanced technology of wireless communication technology has been studied using the tax system. Wireless communications technology logistics management, inventory management, are widely used in the field of port management. Especially, RFID technology, import and export business of logistics costs in the distribution has been hailed as the technology to do. In this paper, logistics information system components, RFID technology is one of the proposed algorithm using the intelligent customs management. Moreover, in this paper, goods purchased from abroad, using the phone anywhere at any time simply to calculate the tariff proposed simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.730-737
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• 2016

Electric utilities may face new threats with increase in electric vehicles (EVs) in the personal automobile market. The peak demand will increase which may stress the distribution network equipment. The focus of this paper is on an adaptive control of smart household appliances by using an intelligent load management system (ILMS). The main objectives are to accomplish consumer needs and prevent overloading of power grid. The stress from the network is released by limiting the peak demand of a house when it exceeds a certain point. In the proposed strategy, for each smart appliance, the customers will set its order/rank according to their own preferences and then system will control the household loads intelligently for consumer reliability. The load order can be changed at any time by the customer. The difference between the set and actual value for each load's specific parameter will help the utility to estimate the acceptance of this intelligent load management system by the customers.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.4
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• pp.133-141
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• 2001

Rapid development in computer and network technology these days has created in environment in which decisions for manufacturing companies can be made in a much broader perspective. Especially, better decisions on production and distribution planning(PDP) problems can be made laking advantage of real time information from all the parties concerned. However, since the PDP problem-a core part of the supply chain management- is known to be the so-called NP-hard problem, so heuristic methods are dominantly used to find out solutions in a reasonable time. As one of those heuristic techniques, many previous studios considered genetic a1gorithms. A standard genetic a1gorithm applies rules of reproduction, gene crossover, and mutation to the pseudo-organisms so the organisms can pass along beneficial and survival-enhancing trails to a new generation. When it comes to representing a chromosome on the problem, it is hard to guarantee an evolution of solutions through classic a1gorithm operations alone, for there exists a strong epitasis among genes. To resolve this problem, we propose a hybrid genetic a1gorithm based on Silver-Meal heuristic. Using IMS-TB(Intelligent Manufacturing System Test-bed) problem sets. the good performance of the proposed a1gorithm is demonstrated.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.369-374
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• 2000

Despite their tilde application of some traditional project management techniques like the Program Evaluation and Review Technique, they lack of learning, one of important factors in many disciplines today due to a static view far prefect progression. This study proposes a framework for estimation by learning based on a Linear Bayesian approach. As a project progresses, we sequentially observe the durations of completed activities. By reflecting this newly available information to update the distribution of remaining activity durations and thus project duration, we can implement a decision support system that updates e.g. the expected project completion time as well as the probabilities of completing the project within talc due date and by a certain date. By Implementing such customized systems, project manager can be aware of changing project status more effectively and better revise resource allocation plans.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.91-98
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• 2000

Despite their wide application of some traditional project management techniques like the Program Evaluation and Review Technique, they lack of learning, one of important factors in many disciplines today, due to a static view for project progression. This study proposes a framework for estimation by loaming based on a Linear Bayesian approach. As a project Progresses, we sequentially observe the durations of completed activities. By reflecting this newly available information to update the distribution of remaining activity durations and thus project duration, we can implement a decision support system that updates e.g., the expected project completion time as well as the probabilities of completing the project within the due bate and by a certain date. By implementing such customized system, project manager can be aware of changing project status more effectively and better revise resource allocation plans.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.337-346
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• 1999

In this paper, we propose the rough set approach to extract trading rules able to discriminate between bullish and bearish markets in stock market. The rough set approach is very valuable to extract trading rules. First, it does not make any assumption about the distribution of the data. Second, it not only handles noise well, but also eliminates irrelevant factors. In addition, the rough set approach appropriate for detecting stock market timing because this approach does not generate the signal for trade when the pattern of market is uncertain. The experimental results are encouraging and prove the usefulness of the rough set approach for stock market analysis with respect to profitability.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.37-47
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• 2011

Current researches in the Cloud focus on the appropriate interactions of cloud components in a large-scale system implementation. However, the current designs do not include intelligent methods like grouping the similar service providers based on their properties and integrating adaptive schemes for load distribution which can promote effective sharing of resource. This paper proposes an efficient virtualization of services by grouping the cloud providers to improve the service provisioning. The grouping of cloud service providers based on a cluster analysis collects the similar and related services in one group. The adaptive load balancing supports the service provisioning of the cloud system where it manages the load distribution within the group using an adaptive scheme. The proposed virtualization mechanism (GRALB) showed good results in minimizing message overhead and throughput performance compared to other methods.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.400-409
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• 2003

Collaborative filtering (CF) recommendation is a knowledge sharing technology for distribution of opinions and facilitating contacts in network society between people with similar interests. The main concerns of the CF algorithm are about prediction accuracy, speed of response time, problem of data sparsity, and scalability. In general, the efforts of improving prediction algorithms and lessening response time are decoupled. We propose a three-step CF recommendation model which is composed of profiling, inferring, and predicting steps while considering prediction accuracy and computing speed simultaneously. This model combines a CF algorithm with two machine learning processes, SOM (Self-Organizing Map) and CBR (Case Based Reasoning) by changing an unsupervised clustering problem into a supervised user preference reasoning problem, which is a novel approach for the CF recommendation field. This paper demonstrates the utility of the CF recommendation based on SOM cluster-indexing CBR with validation against control algorithms through an open dataset of user preference.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.841-846
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• 2010

This paper presents design and implementation of an intelligent video surveillance system. The proposed system has advantages of management efficiency and operation robustness unrelated to working condition compared to conventional CCTV based system. The system hardware is designed and implemented by using commercial chips such as digital media processor and video encoder, video decoder and the functions of software are to analyze temperature distribution of a infrared image and to detect disaster situation such as fire. The required functions are confirmed by testing of the prototype and we verified practicality of the system.

• Journal of the Korea Society for Simulation
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• v.28 no.2
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• pp.15-22
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• 2019

Simulation methods are being studied for various service models that can be used in industries as the development of web technology. DEVS is being used as a tool to simulate through scenarios using various information. In addition, DEVS/WS integrates web-based DEVS models through a distributed computing environment and can be used as tools for high-performance computing and data distribution. This paper describes a method for simulating an intelligent transportation system in DEVS/WS environment. This paper propose dynamic interest management model(DIMM) applied the genetic algorithm, manage efficiently road information of moving node. And, this paper evaluates performance of the dynamic interest management model in comparing to the none interest management model(NIMM). The transmitted messages and simulation time of the DIMM is saved than that of the NIMM.