• Korean Journal of Mathematics
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• v.29 no.1
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• pp.137-167
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• 2021

Spherical fuzzy set (SFS) is also one of the fundamental concepts for address more uncertainties in decision problems than the existing structures of fuzzy sets, and thus its implementation was more substantial. The well-known sine trigonometric function maintains the periodicity and symmetry of the origin in nature and thus satisfies the expectations of the experts over the multi parameters. Taking this feature and the significance of the SFSs into the consideration, the main objective of the article is to describe some reliable sine trigonometric laws (ST L) for SFSs. Associated with these laws, we develop new average and geometric aggregation operators to aggregate the Spherical fuzzy numbers (SFNs). Then, we presented a group decision- making (DM) strategy to address the multi-attribute group decision making (MAGDM) problem using the developed aggregation operators. In order to verify the value of the defined operators, a MAGDM strategy is provided along with an application for the selection of laptop. Moreover, a comparative study is also performed to present the effectiveness of the developed approach.

• Korean Journal of Logic
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• v.12 no.2
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• pp.89-114
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• 2009

We have many causal beliefs, and they play an important role in our decision making. Unlike evidential decision theory, causal decision theory claims that an account of rational choice must use causal beliefs to identify the considerations that make a choice rational. I claim that evidential decision theory is refuted by the original Newcomb's problem but not by the medical Newcomb problem. The latter is taken to be the best example to point out the weakness of evidential decision theory. However, by the explicit statement about causal relations, I argue that the medical Newcomb problem loses its strength in refuting evidential decision theory. With this argument, this paper clarifies the difference between evidential decision theory and causal decision theory.

• Asia pacific journal of information systems
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• v.9 no.1
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• pp.143-163
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• 1999

This study investigates the effect of group size on group performance, here the quality of group decision, Four effects are proposed and tested in a field experimental setting : (1) the relationship between the group size and the distribution of individual's problem-solving ability ; (2) the change of the group decision quality as group size increases ; (3) the relationship between the group decision quality and the quality of the best/worst member as group size increases ; (4) the relationship between the group decision quality and the average quality of individuals in the group as group size increases. Data showed that contrary to the exiting results, group decision quality was not improved with the group size. Rather, it showed a little tendency that group decision quality was worsened with the group size. Data also showed that consensus-oriented group decision making process produced the compromised output. Thus, group decision quality was not better than the average group members'. The opinion of the best member was not accepted. The implications of the findings are discussed for the development of a Korean GSS.

• Journal of Korean Association for Spatial Structures
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• v.3 no.2 s.8
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• pp.77-83
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• 2003

This paper presents decision making method of structural multi-objective fuzzy optimum problem. The data and behavior of many engineering systems are not know precisely and the designer is required to design the system in the presence of fuzziness in the multi-goals, constraints and consequences of possible actions. In this paper, in order to find a satisfactory solution, the membership functions are constructed for the fuzzy objectives subject to the fuzzy constraints, and two approaches are presented by using the different types of fuzzy decision making. Thus, multi-objective fuzzy optimum problem can be converted into single objective non-fuzzy optimum problem and satisfactory solution of the multi-objective fuzzy optimum problem can be found with general optimum programming. Illustrative numerical example of the ten bar truss for minimum weight and minimum deflection is provided to demonstrate the process of finding the solution and the results are discussed.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.201-206
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• 1994

The linear search problem is concerned with finding a hiden target on the real line R. The position of the target governed by some probability distribution. It is desired to find the target in the least expected search time. This problem has been formulated as an optimization problem by a number of authors without making use of Markov Decision Process (MDP) theory. It is the aim of the paper to give a (MDP) formulation to the search problem which we feel is both natural and easy to follow.

• Journal of Korean Academy of Nursing
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• v.40 no.6
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• pp.863-871
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• 2010

Purpose: The purpose of this study was to examine the effects of case-base learning (CBL) using video on clinical decision-making and learning motivation. Methods: This research was conducted between June 2009 and April 2010 as a nonequivalent control group non-synchronized design. The study population was 44 third year nursing students who enrolled in a college of nursing, A University in Korea. The nursing students were divided into the CBL and the control group. The intervention was the CBL with three cases using video. The controls attended a traditional live lecture on the same topics. With questionnaires objective clinical decision-making, subjective clinical decision-making, and learning motivation were measured before the intervention, and 10 weeks after the intervention. Results: Significant group differences were observed in clinical decision-making and learning motivation. The post-test scores of clinical decision-making in the CBL group were statistically higher than the control group. Learning motivation was also significantly higher in the CBL group than in the control group. Conclusion: These results indicate that CBL using video is effective in enhancing clinical decision-making and motivating students to learn by encouraging self-directed learning and creating more interest and curiosity in learning.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.249-273
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• 2004

Finding an optimal solution in MADN[(Multi-Attribute Decision-Making) problems is difficult, when the number of alternatives, or that of attributes is relatively large Most of the existing mathematical approaches arrive at a final solution on the basis of many unrealistic assumptions, without reflecting the decision-maker's preference structure exactly. In this paper we suggest a model that helps us find a group consensus without assessing these parameters in specific cardinal values. Therefore, This research provides a comprehensive Decision Making of the theory and methods applicable to the analysis of decisions that involve risk and multiple criteria attributes. after, The emphasis of the procedure will be on developments from the fields of decisions analysis and utility theory of Taguchi Method. This theoretical development will be illustrated through the discussion of several real-world application and a case study. When the multiple number of decision makers are involved in the decision making procedure, the problem of uncertainties invariably occurs, because of the different views between them. In this paper, New decision making model using Taguchi Method is applied to effectively model the multi-attribute-decision making(MADM) procedure in the uncertainties dominated two area(quantitative and qualitative factors), Quantitative factors evaluation is used Loss Function of Taguchi, qualitative factors evaluation is used 50 ratio by each specialist. thus it can be used for aiding of preferable alternative. as a result, We will be proved efficiency about New decision making model of applied Taguchi Method with Analytical presentation of all the expecting outcomes when a specific strategy or an alternative plan is selected under expecting future environment.

• Journal of the Korean Institute of Rural Architecture
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• v.13 no.2
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• pp.23-30
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• 2011

Even though the existing urban residential district was obsolete and out of date in respects of physical environment, it is maintaining the function of dwelling. It ends up being regenerated as a viable urban residential district when improved the dwelling environment. Therefore, the government has been planning for the residential improvement projects for those areas applying for innovative ideas. But the government programs have often been troubled with people in the process of executing the projects or making a plan. In this respect, two parties couldn't communicate freely about the problem of those areas. So, the problematic issues of the areas should be shared with local residents at the beginning of decision making and the process of workshop participating local residents will be needed for understanding the standpoint of the residents. This study is to explore the potential of residents participating workshop to figure out current problems of the urban residential district in the process of executing the residential improvement project of Nakyang residence area in Sangju city. Upon investigation residents participating workshop is very practical in making a plan, but needs positive participation by resident and a decision making system dealing with the information shared and the understanding gained by participants.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.68-80
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• 2022

Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

• Journal of the Korean Institute of Navigation
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• v.19 no.1
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• pp.33-48
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• 1995

In the process of containerization, the problem of regional maldistribution of container management plan arises seriously due to several factors like a number of unbalances of containers between loading and discharging ports. This study focus on the minimizing cost. This study is composed of two models which in effective management decision making show decision of the number of containers and transfer of empty containers. One is decision of the number of containers which carriers should possess by appropriate forecasting and the other is effective management decision making which includes the transfer of empty containers on calling ports. This study has suggested as follows, First, the Time Series analysis method, especially the "Exponential Smooting with Trend Adjustment" was used to forecast the trade volumes for the designated traffic route. Second, the Time Series analysis method in deciding the optimal number of owned container at the unbalances trade situation between East Bound and West Bound service, most important variables were found such as total traffic volume, the calling interval at a port, the number of days of voyage and the length of stay on shore of container for the optimal number of owned container. Third, effective management decision making model, which makes it possible to analyze the impacts of change in important matters such as lease and positioning policy, and actually influence decision making.on making.