• Korean Business Review
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• v.9
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• pp.158-186
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• 1996

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.27
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• pp.113-119
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• 1993

The purpose of this study is to develop a analytic procedure of the alternatives for the FMS that consist of high-priced facilities. A procedure to analysis the alternatives are as follows. Stage one is procedure to appraise investment alternatives of FMS and devide factors into strategic, analytic, economic viewpoint and draw upon decision making matrix through normalization Stage two is appraise to normalized alternatives using TOPSIS model among multiple attributes decision making models.

• Korean Journal of Organic Agriculture
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• v.30 no.2
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• pp.231-239
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• 2022

The purpose of this study is to provide meaningful information for various stakeholders' decision-making process through forecasting of domestic beef demand. Three different exponential smoothing models were evaluated, and a double exponential smoothing model was used to forecast domestic beef demand based on time-series data, As a result of the forecast, domestic beef consumption is expected to increase by 37,000 to 40,000 tons per year from 2020 to 2025.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1074-1077
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• 1993

The objective of this paper is to develop a fuzzy logic based decision-making system to detect low current faults using multiple detection algorithms. This fuzzy system utilizes a fuzzy expert model which executes an operation without complicated mathematical models. This fuzzy system decides the performance weights of the detection algorithms. The weights and the turnouts of the detection algorithms discriminate faults from normal events. This system can also be a generic group decision-making tool for other areas of power system protection.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.2
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• pp.21-25
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• 2023

The purpose of this study was to compare the performance using multiple regression models to predict the energy consumption of steel industry. Specific independent variables were selected in consideration of correlation among various attributes such as CO2 concentration, NSM, Week Status, Day of week, and Load Type, and preprocessing was performed to solve the multicollinearity problem. In data preprocessing, we evaluated linear and nonlinear relationships between each attribute through correlation analysis. In particular, we decided to select variables with high correlation and include appropriate variables in the final model to prevent multicollinearity problems. Among the many regression models learned, Boosted Decision Tree Regression showed the best predictive performance. Ensemble learning in this model was able to effectively learn complex patterns while preventing overfitting by combining multiple decision trees. Consequently, these predictive models are expected to provide important information for improving energy efficiency and management decision-making at steel industry. In the future, we plan to improve the performance of the model by collecting more data and extending variables, and the application of the model considering interactions with external factors will also be considered.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.65-69
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• 2003

As complex mathematical models are increasingly adopted for business decision-making, difficulties arise in reusing solvers (i.e., model solving algorithms) against diverse models and data sets and thus the collaboration among users (model/solver builders and decision makers) in multiple departments becomes very difficult. To facilitate the solver reuse, this paper adopts the Web services technologies as the base technologies for linking the solvers to the models, both of which are created on different modeling paradigms and different system platforms, in unified system architecture. Specifically, this paper focuses on designing an ontology that represents the interfacing semantics of the model-solver interactions in a general and standardized form. By referring to the ontology, a model management system (MMS) can autonomously suggest a set of compatible solvers and apply them to individual models even though the decision makers are not knowledgeable enough about all the details of the models and the solvers. Thus, this Web services based MMS would improve the reusability of the solvers by relieving the decision makers from the risk of erroneous application of a solver to syntactically and semantically incompatible models and the burden of considerable understanding of model and solver semantics.

• The Journal of Information Systems
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• v.5
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• pp.21-41
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• 1996

Linear programming has become an important tool in decision-making of modern business management. This remarkable growth can be traced to the pioneering efforts of many individuals and research organizations. The popular using of personal computers make it very easy to process those complicated linear programming models. Furthermore advanced linear programming software packages assist us to solve L.P. models without any difficult process. Even though the advanced L.P. professional packages, the needs of more detailed deterministic elements for business decisions have forced us to apply dynamic approaches for more resonable solutions. For the purpose of these problems applying to the "Mathematica" packages which is composed of mathematic tools, the simplex processes show us the flexible and dynamic decision elements included to any other professional linear programming tools. Especially we need proper dynamic variables to analyze the shadow prices step by step. And applying SAS(Statistical Analysis System) packages to the L.P. problems, it is also one of the best way to get good solution. On the way trying to the other L.P. packages which are prepared for Spreadsheets i.e., MS-Excel, Lotus-123, Quatro etc. can be applied to linear programming models. But they are not so much useful for the problems. Calculating simplex tableau is an important method to interpret L.P. format for the optimal solution. In this paper we find out that the more detailed and efficient techniques to interpret useful software of mathematica and SAS for business decision making of linear programming. So it needs to apply more dynamic technique of using of Mathematica and SAS multiple software to get more efficient deterministic factors for the sophiscated L.P. solutions.

• Journal of the military operations research society of Korea
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• v.27 no.2
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• pp.37-55
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• 2001

The main purpose of this study is to review the current system and to develop a decision support system for evaluating the priorities among those possible alternatives in the army facility enterprise. This paper also provides an information system which can be effectively applied to various criteria and stages in decision making process such as Planning and Programming phases in PPBEES. The model base of decision support systems uses the concepts of the analytic hierarchy process along with the supplementary techniques such as TOPSIS and 0-1 integer programming. Both AHP and TOPSIS are used scoring approaches in the Planning phase and IP is induced at the Programming phase to give GO/NO-GO solution for each project. We use Expert Choice, Excel and LINDO s/w's to implement a prototyped model. The proposed methodology in this paper enables the decision makers to evaluate the priority based on quantitative and qualitative data in a systematic way.

• Proceedings of the Korea Association of Information Systems Conference
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• 2002.11a
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• pp.289-312
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• 2002

This study suggests the Link weight analysis approach to choose input variables and an integrated model to make more accurate bankruptcy prediction model. the Link weight analysis approach is a method to choose input variables to analyze each input node's link weight which is the absolute value of link weight between an input nodes and a hidden layer. There are the weak-linked neurons elimination method, the strong-linked neurons selection method in the link weight analysis approach. The Integrated Model is a combined type adapting Bagging method that uses the average value of the four models, the optimal weak-linked-neurons elimination method, optimal strong-linked neurons selection method, decision-making tree model, and MDA. As a result, the methods suggested in this study - the optimal strong-linked neurons selection method, the optimal weak-linked neurons elimination method, and the integrated model - show much higher accuracy than MDA and decision making tree model. Especially the integrated model shows much higher accuracy than MDA and decision making tree model and shows slightly higher accuracy than the optimal weak-linked neurons elimination method and the optimal strong-linked neurons selection method.

• Journal of Korean Home Economics Education Association
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• v.9 no.1
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• pp.111-131
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• 1997

The purpose of this study is to develop the lesson model for high school students to improve their abilities as consumer. In the method of the research, the contents on consumer education of the 8 kinds of Home Economics textbooks are reconstructed into the areas of decision-making, financing, reasonable purchasing, and consumer citizenship. The consumer’s ability to be developed in the areas of decision-making, financing, reasonable purchasing, and consumer citizenship is set up as follows： 1) The establishment of the sound consumer morality and values, the ability of independent decision-making, the critical ability, and the problem-solving ability. 2) The ability of research on social, cultural and economic values, and the ability to estimate one’s own short-term and long-term life plan. 3) The ability of reasonable purchase. 4) The ability to participate in a consumer movement, and the ability to take good care of environment. Subsequently, 9 lesson models for the student to improve the consumer’ability are developed.