• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.535-545
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• 2022

The purpose of this study is to classify the various problems in surface road according to their severity and to propose a priority decision making process for road policy makers. For this purpose, the road problems reported by Cheok-cheok app were classified, and the EPDO was adopted and calculated as an index of their severity. To test applicability of the proposed process, some images of road problems reported by the app were classified and annotated, and the Deep Learning was used for machine learning of the curated images, and then the other images of road problems were used for verification. The detecting success rate of the road problems with high severity such as road kills, obstacles in a lane, road surface cracks was over 90%, which shows the applicability of the proposed process. It is expected that the proposed process will make the app possible to be used in the filed to make a priority decision making by classifying the level of severity of the reported road problems automatically.

• 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Even though the existing urban residential district was obsolete and out of date in respects of physical environment, it is maintaining the function of dwelling.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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.6
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• pp.692-703
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• 2014

The purpose of this study is to clarify the problems and causes of OSC system of the KCG. In the disaster of sea, the possibility that could expect a reasonable decision making is low. The study has carried out for the different point of view of the problems. The problems have been revealed through the theory and analysis of structural and non-structural aspects for the OSC system, such as inefficient organization system, failure of reasonable decision making, lack of communication with the field. The conclusions of the study have been proposed such as an advanced On-Scene Command system, efficient organization, the training of professional staff, the creating of open organizational culture.

• Informatization Policy
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• v.26 no.3
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• pp.3-35
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• 2019

In the fourth industrial revolution age, because of advance in the intelligence information technologies, the various roles of AI have attracted public attention. Starting with Google's Alphago, AI is now no longer a fantasized technology but a real one that can bring ripple effect in entire society. Already, AI has performed well in the medical service, legal service, and the private sector's business decision making. This study conducted an exploratory analysis on the possibilities and issues of AI-driven policy decision making in the public sector. The three research purposes are i) could AI make a policy decision in public sector?; ii) how different is AI-driven policy decision making compared to the existing methods of decision making?; and iii) what issues would be revealed by AI's policy decision making? AI-driven policy decision making is differentiated from the traditional ways of decision making in that the former is represented by rationality based on sufficient amount of information and alternatives, increased transparency and trust, more objective views for policy issues, and faster decision making process. However, there are several controversial issues regarding superiority of AI, ethics, accountability, changes in democracy, substitution of human labor in the public sector, and data usage problems for AI. Since the adoption of AI for policy decision making will be soon realized, it is necessary to take an integrative approach, considering both the positive and adverse effects, to minimize social impact.

• Journal of the Korea Safety Management & Science
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• v.6 no.4
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• pp.107-122
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• 2004

This study aims to examine the usefulness on the Evaluation Process for the Feasibility & Priority of A Certain Public Projects. and the Methodology used AHP(Analytic Hierarchy Process) which used pairwise comparisons of the alternatives and criteria for solving discrete alternative multicriteria decision problems. In this paper, we present a similar phenomenon, rank reversal problem, when we apply the AHP to group decision making process. The problem is identified by an example problem in that the previous rank order of Public Projects choices. we also present three different methods to prevent the undesirable characteristic of the original AHP in appling to Decision Making Process.

• 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.

• Proceedings of the Korean Society of Rural Planning Conference
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• 1998.10a
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• pp.5-8
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• 1998

South korean self support rate fer the grain product is less than 25%, 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 eft. 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.71-76
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• 2011

The problem of decision making under imprecise environments are widely spread in real life decision situations. We present a method of object recognition from imprecise multi observer data, which extends the work of Roy and Maji [J Compu. Appl. Math. 203(2007) 412-418] to generalized intuitionistic fuzzy soft set theory. The method involves the construction of a comparison table from a generalized intuitionistic fuzzy soft set in a parametric sense for decision making.

• 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.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.277-280
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• 2006

Most real world design evaluation and risk-based decision support combine quantitative and qualitative (linguistic) variables. Decision-making based on conventional mathematics that combines qualitative and quantitative concepts always exhibit difficulty in modelling actual problems. The successful selection process for choosing a design/procurement proposal is based on a high degree of technical integrity, safety levels and low costs in construction, corrective measures, maintenance, operation, inspection and preventive measures. However, the objectives of maximising the degree of technical performance, maximising the safety levels and minimising the costs incurred are usually in conflict, and the evaluation of the technical performance, safety and costs is always associated with uncertainties, especially for a novel system at the initial concept design stage. In this paper, a design-decision support framework using a composite structure methodology grounded in approximate reasoning approach and evidential reasoning method is suggested for design evaluation of machinery space of a ship engine room at the initial stages. It is a Multiple Attribute Decision-Making (MADM) or Multiple Criteria Decision Making (MCDM) framework, which provides a juxtaposition of cost, safety and technical performance of a system during evaluation to assist decision makers in selecting the winning design/procurement proposal that best satisfies the requirement in hand. An illustrative example is used to demonstrate the application of the proposed framework.