• 한국경영과학회지
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• 제30권1호
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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.

• 대한안전경영과학회지
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• 제6권2호
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• pp.177-186
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• 2004

Decision analysis has becomes an important technique for decision making in the face of uncertainty. It is characterized by enumerating all the available courses of action, identifying the payoffs for all possible outcomes, and quantifying the subjective probabilities for the all possible random events. When the data are available, decision analysis becomes a powerful tool for determining an optimal course of action. We study the multi-attribute decision making in a compensatory models. In this paper, we use the entropy methods in weights calculating. For the purpose of making optimal decision, the data of five different car models are used. For computing, we used Visual Numerica Version 1.0 software package.

• Asia pacific journal of information systems
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• 제14권2호
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• pp.37-59
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• 2004

Team decision making is a collective behavior that needs to be understood by considering properties belonging to team and individual member domains together. This paper introduces a conceptual model called "Dual-Level(DL)" model that describes a team decision-making process in terms of team level, member level, and the relationship between them. The team-level view explains the decision-making process by considering the team as a wholeand divides the process into three stages: Problem Conceptualization, Alternative Generation, and Selection. The member-level view describes what happens to individual members when they go through the group process and splits it into the five phases: Individual Cognitive Mapping, Problem Decomposition, Subproblem Session, Subproblem Integration, and Team Decision. The DL model works as a theoretical framework to explore team decision making by using a set of computational models of team design and team members. In practice, the conceptual framework is used to build a computational model of decision making team, called "Team-Soar."

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2942-2960
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• 2022

The core of cognitive radio is the problem concerning intelligent decision-making for communication parameters, the objective of which is to find the most appropriate parameter configuration to optimize transmission performance. The current algorithms have the disadvantages of high dependence on prior knowledge, large amount of calculation, and high complexity. We propose a new decision-making model by making full use of the interactivity of reinforcement learning (RL) and applying the Q-learning algorithm. By simplifying the decision-making process, we avoid large-scale RL, reduce complexity and improve timeliness. The proposed model is able to find the optimal waveform parameter configuration for the communication system in complex channels without prior knowledge. Moreover, this model is more flexible than previous decision-making models. The simulation results demonstrate the effectiveness of our model. The model not only exhibits better decision-making performance in the AWGN channels than the traditional method, but also make reasonable decisions in the fading channels.

• 대한산업공학회지
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• 제33권3호
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• pp.290-302
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• 2007

This paper introduces several decision-making problems that need to be solved in order to facilitate the efficient operation of container terminals. These decision-making problems include the berth planning problem, the quay crane scheduling problem, the unload/load sequencing problem, the yard allocation problem, and the short-term scheduling of transporters and yard cranes. These problems can be classified into strategic decision problems, tactical decision problems, and real time operational decision problems. This paper proposes definitions of the problems that can be used to develop mathematical models for the problems.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2006년도 춘계공동학술대회
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• pp.123-131
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• 2006

Multi-criteria decision making is deducing the relative importance in the criterion of decision making and each alternative which is able to making a variety of choices measures the preferred degree in the series of low-raking criterions. Moreover, this is possible by synthesizing them systematically. In general, a fundamental problem decision maker solve for multi-criteria decision making is evaluating a set of activities which are considered as the target logically, and this kind of work is evaluated and synthesized by various criterions of the value which a chain of activities usually hold in common. In this paper, we are the eigenvector methods in weights calculating. For the purpose of making optimal decision, the data of five different car models are used. For computing, we used Visual Numerica Version 1.0 software package.

• 대한토목학회논문집
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• 제34권2호
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• pp.645-654
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• 2014

현재 우리나라 일반국도의 포장관리시스템(PMS: Pavement Management System)은 세계은행(World Bank)이 주도한 HDM (Highway Development and Management)-4를 사용하여 유지보수 의사결정의 기초 자료로 사용하고 있으나, 과다한 입력변수와 모형의 불확실성 등으로 인해 국내 실정에 적합한 경제성 분석모형이 필요하게 되었으며, 대부분의 선진국의 경우에는 각 지역과 국가에 맞는 PMS 시스템을 구축하여 운영하고 있다. 따라서 본 연구에서는 우리나라 실정에 맞고 효율적인 국도의 도로 및 포장관리를 위한 의사결정시스템을 개발하기 위한 연구로써 시스템 개발에 필요한 구성요소, 공용성 모형 개발, 각 요소별 활용가능한 원단위, 기준 등의 지표 정의 및 종류, 특성들을 분석, 정리하고 경제성 평가를 통해 최적 의사결정을 위한 시스템(S/W) 개발을 목적으로 하였다. 포장관리를 위해 개발한 의사결정시스템의 구성요소는 크게 1)도로, 교통, 사회경제 지표 등의 DB, 2) 도로포장상태의 공용성 모형, 3)도로포장상태에 따른 차량속도변화 모형, 4)경제성 평가 모형, 5) 의사결정지원 시스템으로 구성되며, 개발된 시스템의 검증을 위해 사례 구간을 대상으로 한 분석결과도 함께 제시하였다. 그러나 장래 확률적 특성을 고려한 공용성 모형의 개발과 의사결정을 위한 지표 개발에 대해서는 추가적인 연구가 필요할 것으로 판단된다.

• 대한간호학회지
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• 제31권5호
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• pp.846-857
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• 2001

This study was conducted to study on 1) What is nursing students' experience of ethical problems involving nursing practice\ulcorner 2) What is nursing students' experience of using ethical decision-making models\ulcorner Method: In order to answer these two questions, we selected 97 senior baccalaureate nursing students from two Korean universities using a conceptual framework and method of content analysis. Result: From 97 ethical problems emerged five content categories, the largest being ethical problems involving health professionals (69%); the basic nature of the nursing students' experience of ethical problems consisted of conflict, resolution, and rationale; 94% of the students stated that using an ethical decision- making model was helpful. Conclusion: Although additional research is needed, these findings have important implications for nursing ethics education and practice.

• 농촌지도와개발
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• 제4권1호
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• pp.329-337
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• 1997

Normative models for explaning the career decision-making process are not sufficient to enable the career counselor to help a client understand and influence the factors affecting his career. Actually, the particular people and life events that are unpredictable and subject to chance often influence on career behavior. Therefore, it is needed the development of a models of career decision-making that recognizes both normative and chance influences. The focus in this article is on the development of career decision-making within various lift contexts and the recognition that individuals may prepare themselves to use unexpected opportunities in the career decision-making process.

• Asia pacific journal of information systems
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• 제10권3호
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• pp.105-120
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• 2000

The objective of this paper is to show how team study can be advanced with the aid of a current computer technology, that is distributed Artificial Intelligence(DAI). Studying distributed problem solving by using groups of artificial agents, DAI can provide important ideas and techniques for the study of team behaviors like team decision making. To demonstrate the usefulness of DAI models as team research tools, a DAI model called 'Team-Soar' was built and a simulation experiment done with the model was introduced, Here, Team-Soar models a naval command and control team consisting of four members whose mission was to identify the threat level of aircraft. The simulation experiment was performed to examine the relationships of team decision scheme and member incompetence with team performance. Generally, the results of the Team-Soar simulation met expectations and confirmed previous findings in the literature. For example, the results support the existence of main and interaction effects of team decision scheme and member competence on team performance. Certain results of the Team-Soar simulation provide new insights about team decision making, which can be tested against human subjects or empirical data.