• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.165-168
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• 1999

The support or automation of various kinds of intelligent work is urged at large, integrated control centers. Given this demand, a decision making system for wash timing of polluted insulators, applying the Bayesian rule theory, has been developed in order to support maintenance work in the power system. The results of this system application revealed that exact wash timing of the insulators could be determined automatically, equivalent in precision to judgement by skilled operators, thus contributing to further work efficiency.

• Journal of Korean Society of Rural Planning
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• v.4 no.2
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• pp.103-116
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• 1998

South Korean self support rate for the grain product is less than 25oyo, and depends on the imported product for the national food supply. Therefore, there is imminent need for development of agricultural decision support system using GIS which provides various useful informations for a more accurate agricultural policy making. Agricultural decision making processes are complex due to complicated current international political situations, and the erratic weather condition like that Elnino, flood and drought etc. Hence, global scale GIS and analytical applications has implemented for solving the agricultural problems above mentioned in this study. As the results, the executable decision process with GIS developed well adopted for the rice cultivable area estimation in the world.

• Asia pacific journal of information systems
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• v.6 no.1
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• pp.39-74
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• 1996

Most of the research on a group decision support system [GDSS] has focused on directly examining its effect on the decision outcomes. Under this research framework, however, the role of group interaction process is largely ignored. This study focuses on the effect of the group interaction process on decision-making performance when a GDSS is used as the only medium for group interaction. Specifically, this study sought to determine whether significant relationships exist between the quality of the decision and the decision functions, contingent phases, and different decision paths. Natural interaction processes of decision -making groups was simulated in an experimental setting in which volunteer subjects from several business classes were assigned to dispersed three-person groups undertook the experimental task via a decision network. A baseline GDSS was developed for this setting. The results of this study confirmed earlier studies in a non - GDSS setting to suggest significant effects of decision functions and contingent phases on the quality of decision but no significant relationship between decision path and the quality of group decision.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.4
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• pp.13-23
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• 2007

This paper focuses on providing a practical approach for decision making in Performance-Based Design (PBD). Satisfactory performance is defined by several performance objectives that place limits on direct (monetary) loss and on a tolerable probability of collapse. No specific limits are placed on conventional engineering parameters such as forces or deformations, although it is assumed that sound capacity design principles are followed in the design process. The proposed design procedure incorporates different performance objectives up front, before the structural system is created, and assists engineers in making informed decisions on the choice of an effective structural system and its stiffness (period), base shear strength, and other important global structural parameters. The tools needed to implement this design process are (1) hazard curves for a specific ground motion intensity measure, (2) mean loss curves for structural and nonstructural subsystems, (3) structural response curves that relate, for different structural systems, a ground motion intensity measure to the engineering demand parameter (e.g., interstory drift or floor acceleration) on which the subsystem loss depends, and (4) collapse fragility curves. Since the proposed procedure facilitates decision making in the conceptual design process, it is referred to as a Design Decision Support System, DDSS. Implementation of the DDSS is illustrated in an example to demonstrate its practicality.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2106-2112
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• 1999

In decision-making, information is the thing manufactured as the useful type for decision -making. We can improve the efficiency of decision-making by elimination of unnecessary information. Rough set is the theory that can classify and reduce the unnecessary. But the reduction process of rough set becomes more complex according to the number of attribute and tuple. After eliminating of the dispensable attributes using $\chi$2 and rough set, the indispensable attributes are used for the units of input layers in neural network. This rough-neural network can support more correct decision-making of neural network.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.283-291
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• 2005

The development of mobile applications is fast in recent years. However, nearly all applications are for messaging, financial, locating services based on simple interactions with mobile users because of the limited screen size, narrow network bandwidth, and low computing power. Processing an algorithm for supporting a group decision process on mobile devices becomes impossible. In this paper, we introduce the mobile-oriented simple interactive procedure for support a group decision making process. The interactive procedure is developed for multiple objective linear programming problems to help the group select a compromising solution in the mobile Internet environment. Our procedure lessens the burden of group decision makers, which is one of necessary conditions of the mobile environment. Only the partial weak order preferences of variables and objectives from group decision makers are enough for searching the best compromising solution. The methodology is designed to avoid any assumption about the shape or existence of the decision makers's utility function. For the purpose of the experimental study of the procedure, we developed a group decision support system in the mobile Internet environment, MOBIGSS　and applied to an allocation problem of investor assets.

• Asia pacific journal of information systems
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• v.6 no.2
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• pp.5-17
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• 1996

There are various cases that we vote for making a decision or combining ideas (i.e. human being's opinions) in group meetings. Group Decision Support System(GDSS) provides us with a number of voting methods for decision making or aggregation of the ideas. It is generally difficult to select a voting method appropriate for given a meeting situation, without any aid of experts or computers having a knowledge on voting. In this paper we propose a supporting system for selecting an appropriate voting method. Since the selected method is recommended to the facilitator of GDSS, a part of time and effort related with the voting would be reduced. The knowledge in the system is represented as rules that are inductively generated from examples of voting. We used UNiK-INDUCE with ID3 algorithm so as to learn, which is a tool of developing expert systems.

• Journal of Korean Society for Quality Management
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• v.34 no.3
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• pp.31-40
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• 2006

Companies had to be more intelligent in order to survive in the rapidly changing environments. We need to make a decision to build the Information System to support the managers in their decision making. That is the reason many companies are tend to have Business Intelligence Systems. But, how can we know the new system would be better than the old system in making us intelligent? The answer is we can do it with the concept of Intelligence Density. In this study, Intelligence Density concept will be introduced, and the way how it can be applied to the information system will be presented. I think Intelligence Density should be studied more to help managers make right decisions for the DSS implementation.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.183-192
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• 2005

Recently, community computing has been proposed for group formation and group decision-making. However, legacy community computing systems do not support group need identification for ad hoc group formation, which would be one of key features of ubiquitous decision support systems and services. Hence, this paper aims to provide a multi-agent based methodology to enable nomadic community computing which supports ad hoc need identification and group formation. Focusing on supporting group decision-making of relatively small sized multiple individual in a community, the methodology copes with the following three characteristics: (1) ad hoc group formation, (2) context-aware group need identification, and (3) using mobile devices working in- and out-doors. NAMA-US, an RFID-based prototype system, has been developed to show the feasibility of the idea proposed in this paper.

• Journal of Korean Port Research
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• v.13 no.2
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• pp.255-266
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• 1999

The purpose of this paper is to describe the design of the decision support system for container terminal ship planning and to introduce the implemented system. The ship planning in container terminals consists of three major decision processes -the working schedule of gantry cranes the discharging sequence of inbound containers the loading position and sequence of outbound containers. For making these decision the proposed system can provide two ship planning modes the interactive planning mode with user-friendly GUI and the automated planning made. To implement the automated planning routine we acquired the planning rules from the expert planner in container terminals and developed an expert system based on the rules. Finally we evaluated the system developed and the potential for commercialization by using container terminal data.