• Asia pacific journal of information systems
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• v.13 no.2
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• pp.105-117
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• 2003

As E-commerce is getting more popular, consumers faces more decision complexity than ever before because they can get greater alternative choices. Futhermore, consumers are sometimes motivated to expand effort in making a good decision in the case of relatively important and non-routine decison, such as buying a house or car. Thus, a buying decision support function is required to help consumers make decisions that have the greatest effects on consumer's lives. We develop a propotype system of a web-based buying decision support system for a cyber shopping mall. A buying decision of a consumer is a multi-attribute decision problem and is supported using analytic hierarchy process model. The system was implemented using HTML, Java, Java applet, JSP.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.75-94
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• 2005

Research in the decision sciences has continued to develop a variety of mathematical models as well as software tools supporting corporate decision-making. Yet. in spite of their potential usefulness, the models are little used in real-world decision making since the model solution processes are too complex for ordinary users to get accustomed. This paper proposes an intelligent and flexible model-solver integration framework that enables the user to solve decision problems using multiple models and solvers without having precise knowledge of the model-solution processes. Specifically, for intuitive model-solution, the framework enables a decision support system to suggest the compatible solvers of a model autonomously without direct user intervention and to solve the model by matching the model and solver parameters intelligently without any serious conflicts. Thus, the framework would improve the productivity of institutional model solving tasks by relieving the user from the burden of leaning model and solver semantics requiring considerable time and efforts.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.368-368
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• 2000

In this paper, we present forecasting ozone concentration with decision support system. Since the mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, modeling of ozone prediction system has many problems and results of prediction are not good performance so far. Forecasting ozone concentration with decision support system is acquired to information from human knowledge and experiment data. Fuzzy clustering method uses the acquisition and dynamic polynomial neural network gives us a good performance for ozone prediction with ability of superior data approximation and self-organization.

• IE interfaces
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• v.20 no.4
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• pp.488-497
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• 2007

In order to provide appropriate decision supports in medical domain, it is required that clinical knowledge should be implemented in a computable form and integrated with hospital information systems. Healthcare organizations are increasingly adopting tools that provide decision support functions to improve patient outcomes and reduce medical errors. This paper proposes a process centric clinical decision support system based on medical knowledge. The proposed system consists of three major parts - CPG (Clinical Practice Guideline) repository, service pool, and decision support module. The decision support module interprets knowledge base generated by the CPG and service part and then generates a personalized and patient centered clinical process satisfying specific requirements of an individual patient during the entire treatment in hospitals. The proposed system helps health professionals to select appropriate clinical procedures according to the circumstances of each patient resulting in improving the quality of care and reducing medical errors.

• The KIPS Transactions:PartA
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• v.10A no.5
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• pp.519-528
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• 2003

Container terminals need decisions in the course of daily-24 hour and 365 day - operations, and all these decisions are inter-related. The ultimate goal of Decision Support System is to minimize ship loading/unloading time, resources used to handle the workload, and congestion on the roads inside the terminal. It is also to make the best possible use of the storage space available. Therefore, the necessity of decision support tools are emphasized to enhance the operational efficiency of container shipping terminals more, because of limits and complexity of these decisions. So, in thia paper, we draw evaluation items for Decision Support Systems and suggest optimization strategy of evaluation items which have the greatest influence on Decision Support system, that is, yard stacking allocation, RTGC deployment among blocks, and YT allocation to QCs. We also estimate the efficiency of Decision Support System design by simulation using G2 language, comparing ship loading/unloading time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.958-965
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• 2003

The rapidly changing business environment has required cooperation and coorduiation among functional units n organizations which should Involve group decision-making processes Although many group derision-making support tools and methods have provided the collaborative capabilities for organizational members, they often lack features supporting the dynamic complexity issue frequently occurring at group decision-making processes This study proposes system dynamics modeling as a group decision-making support tool to deal with the group derision-making tasks having properties of dynamic complexity in terms of cognitive fit theory.

• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.83-93
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• 2007

This paper gives an attempt to build a decision support tool linked with a simulation software called ARENA for evaluating and comparing the performance of the push and pull material driven strategies operating in the flow shop environment with a bottleneck resource as the shop's constraint. To be fair for such evaluation, the comparison must be made fairly under the optimal setting of both systems' operating parameters. In this study, an optimal-seeking heuristic algorithm, Genetic Algorithm (GA), is employed to suggest a systems' best design based on the economic consideration, which is the profit generated from the system. Results from the study have revealed interesting outcomes, letting us know the strength and weakness of the push and pull mechanisms as well as the effect of each operating parameter to the overall system's financial performance.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.58-63
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• 2002

Recently a new multi-attribute analysis method is one of the evident areas of important points in the decision support system analysis. The area of decision support system may be broken into three primary area: idea generation, multi-attribute structured analysis method, and the integration of the results of analysis. This research developed an internet/intranet-based solution builder for a three-step decision support system in the view of 1) brainstorming for the idea generation, 2) analytic hierarchy process as a multi-attribute structured analysis method and 3) aggregating logic model to integrate the results of individual analysis. A computer program is developed and demonstrated in internet/intranet-based decision problem. This solution builder provides decision makers a good tool for remote group decision making.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.117-124
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• 2019

Recently, medical IT solutions are being provided on a distributed environment basis. In Korea, the necessity of developing a clinical decision support system that can share medical information in a distributed environment has been recognized and studied. The existing clinical decision support system is being built using only medical information of its own within the hospital. This makes it difficult for existing systems to achieve good results in terms of efficiency and accuracy of decision support. In order to solve these limitations, this paper proposes a design and implementation method of clinical decision support system based on common data model in medical field. To explain the application process of the proposed model, we describe the development scenario of the clinical decision support system for the diagnosis of colorectal cancer. We also propose the essential requirements for the development of successful clinical decision support systems. Through this, it is expected that it will be possible to develop clinical decision support system that can be used in various hospitals and improve the efficiency and accuracy of the system.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3045-3051
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• 1997

Generally, multi-criteria decisions are made by group of people because of their complexity. In the existing fuzzy aggregation method, the operators using minimum, maximum and average are used to aggregate the viewpoints of many staffs. These methods have problems in that they do not reflect the decision situation in the decision process. In order to solve these problems we propose a new fuzzy multi-criteria decision support systems model that aids the decision maker to aggregate the viewpoints of many staffs according to the decision situation. Moreover, we design the algorithms which can be used in the fuzzy multi-criteria decision support systems and develop its prototying system.