• 한국항행학회논문지
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• 제27권6호
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• pp.690-698
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• 2023

현재 수많은 공항에서는 공항 협력적 의사결정지원체계 (A-CDM; airport cooperative decision making system) 도입 후 이를 기반으로 공항 이해관계자들의 정보 공유 및 결정이 가능해졌다. 이는 곧 항공기 처리시간을 최적화하고 공항 운영의 효율성을 증가시켰다. 버티포트 또한 이러한 효율성 증대를 위한 방안이 필요하다. 기존 공항의 항공기에 비해 UAM 기체는 도심 속을 비행하는 새로운 항공교통체계로써 도심 내 교통체증을 겪지 않으면서 빠르게 이동하고 싶은 사용자의 수요가 큰 비중을 차지할 것이다. 그렇기에 지연이나 뜻하지 않은 결항은 사용자의 만족도를 크게 낮추게 된다. 이러한 점을 보완하기 위해 버티포트와 UAM의 특성에 맞게 의사결정지원체계의 기준을 수립하여 V-CDM을 도입한다면 버티포트에서의 UAM에 대한 효율적인 운영이 가능해질 것이다. 본 논문에서는 버티포트의 이해관계자를 정의하고 A-CDM을 기반으로 V-CDM이 어떤 방식으로 운영되어야 하는가에 대한 방안을 제시하였다.

• 한국생산제조학회지
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• 제19권1호
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• pp.94-100
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• 2010

Nowadays, several nontraditional machining(NTM) processes are widely used to machine a complex and accurate shape part of hard materials, such as titanium, ceramics, high strength temperature resistant and refractory materials which are difficult to machine and having high strength, hardness, toughness. Machining of these complex shapes in such materials by traditional machining processes are very difficult. The NTM processes is important in the areas of micro- and nano scale machining, where high accuracy and superior surface characteristics are required, which can only be achieved using these NTM processes. So, for effective selection of different NTM processes, careful decision making for a given NTM application is often necessary. An appropriate NTM process for a given material and shape condition is very difficult for the novice engineers. In this paper, an expert system based on an analytic network process(ANP) is suggested for a best selection of NTM process in a NTM application considering an prior interdependency effect among various factors.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2005년도 공동추계학술대회
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• pp.557-567
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• 2005

The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore are, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiperson criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interaction may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2007년도 추계 종합학술대회 논문집
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• pp.183-187
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• 2007

고도의 지식 기반사회인 현대사회에서 과학적 지식과 기술 혁신은 개인과 사회, 그리고 국가의 경제 발전과 경쟁력을 위한 필수적 요소로서 자리매김해 왔다. 그러나 이와 동시에 줄기세포연구, 유전자조작기술 등 기술혁신에 따른 잠재적 위험성은 사회적 불안 및 갈등요소로도 작용하고 있다. 기술에 대한 불확실성이 증가하고 사회가 다원화하면서 과학기술정책의 의사결정과정도 기존의 톱다운 방식인 '거버먼트(Government)'에서 점차적으로 '거버넌스(Governance)로 옮겨가고 있다. 다양한 사회 구성원의 참여로 의사결정이 이루어지는 거버넌스는 복잡한 사회 현상들에 대한 다원적 접근을 가능하게 한다. 본고에서는 거버넌스, 특히 기술혁신과 관련된 리스크 거버넌스를 중심으로 과학기술지식을 기반으로 한 의사결정모델을 살펴보고, 글로벌 시대에 과학기술과 사회의 지속가능한 발전을 위한 거버넌스 체계를 모색해보고자 한다.

• 한국IT서비스학회지
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• 제13권2호
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• pp.133-149
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• 2014

It is unavoidable to provide products that meet customers' needs and wants so that firms may survive under the competition in this globalized market. This paper focuses on how to provide levels for attributes that compse product so that firms may give the best products to customers. In particular, its main issue is how to determine common attributes and the others with their appropriate levels to maximize firms' profits, and how to construct a decision support system to ease decision makers' decisons about optimal common attribute selection using the Semantic Web and SWCL technologies. Parameter data in problems and the relationships in the data are expressed in an ontology data model and a set of constraints by using the Semantic Web and SWCL technologies. They generate a quantitative decision making model through the automatic process in the proposed system, which is fed into the solver using the Logic-based Benders Decomposition method to obtain an optimal solution. The system finally provides the generated solution to the decision makers. This presentation suggests the opportunity of the integration of the proposed system with the broader structured data network and other decision making tools because of the easy data shareness, the standardized data structure and the ease of machine processing in the Semantic Web technology.

• 한국군사과학기술학회지
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• 제15권1호
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• pp.1-8
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• 2012

Obstacle detection is much studied by using sensors such as laser, vision, radar and ultrasonic in path planning for UGV(Unmanned Ground Vehicle), but not much reported about its characterization. In this paper not only an obstacle classification method using 2-dimensional LMS(Laser Measurement System) but also a decision making method whether to avoid or traverse the obstacle is proposed. The basic idea of decision making is to classify the characteristics by 2D laser scanned data and intensity data. Roughness features are obtained by range data using a simple linear regression model. The standard deviations of roughness and intensity data are used as measures for decision making by comparing with those of reference data. The obstacle classification and decision making for the UGV can facilitate a short path to the target position and the survivability of the robot.

• 한국시스템다이내믹스연구
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• 제9권1호
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• pp.57-71
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• 2008

This research paper describes a complex and vague settings in which organization makes a decision and explains a role of decision maker's learning process. The original paper, written by Cohen, March, Olsen in 1972, said that all members of organization depended on the technology taken through trials and errors, which is the 'learning' process literally. But they intended to exclude the learning process in their simulation model because their PORTRAN model couldn't replicate the learning concept. As a result, they couldn't explain how all agents of garbage can simulation model resolve the problem dynamically. To overcome this original paper's limitations, we try to rebuild a learning process simulation model using by system dynamics approach that can capture the linkage between organization leanings and agents-based decision-makings. Our learning simulation results reveal two points. First, decision maker's leanings process improves the efficiency of decision making in complex situation. Second, group learning shows a superior efficiency to an individual learning because group members share organizational memory and energy.

• 산업경영시스템학회지
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• 제46권3호
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• pp.109-122
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• 2023

As platforms become primary decision making tools, platforms for decision have been introduced to improve quality of decision results. Because, decision platforms applied augmented decision-making process which uses experiences and feedback of users. This process creates a variety of alternatives tailored for users' abilities and characteristics. However, platform users choose alternatives before considering significant quality factors based on securing decision quality. In real world, platform managers use an algorithm that distorts appropriate alternatives for their commercial benefits. For improving quality of decision-making, preceding researches approach trying to increase rational decision -making ability based on experiences and feedback. In order to overcome bounded rationality, users interact with the machine to approach the optional situation. Differentiated from previous studies, our study focused more on characteristics of users while they use decision platforms. This study investigated the impact of quality factors on decision-making using platforms, the dimensions of systematic factors and user characteristics. Systematic factors such as platform reliability, data quality, and user characteristics such as user abilities and biases were selected, and measuring variables which trust, satisfaction, and loyalty of decision platforms were selected. Based on these quality factors, a structural equation research model was created. A survey was conducted with 391 participants using a 7-point Likert scale. The hypothesis that quality factors affect trust was proved to be valid through path analysis of the structural equation model. The key findings indicate that platform reliability, data quality, user abilities, and biases affect the trust, satisfaction and loyalty. Among the quality factors, group bias of users affects significantly trust of decision platforms. We suggest that quality factors of decision platform consist of experience-based and feedback-based decision-making with the platform's network effect. Through this study, the theories of decision-making are empirically tested and the academic scope of platform-based decision-making has been further developed.

• International Journal of Computer Science & Network Security
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• 제23권6호
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• pp.49-58
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• 2023

Renewable energy is not a new terminology. One of the fastest growing renewable energies is solar energy. The implementation of solar energy provides several advantages including the reduction of some of the environmental risks of fossil fuel consumption. This research elaborated the importance of the adaption of solar energy by developing a spatial decision support system (SDSS), while the Residential Solar Energy Adoption (RSEA) is an instantiation artifact in the form of an SDSS. As a GIS web-based application, RSEA allows stakeholders (e.g., utility companies, policymakers, service providers homeowners, and researchers) to navigate through locations on a map interactively. The maps highlight locations with high and low solar energy adoption potential that enables decision-makers (e.g., policymakers, solar firms, utility companies, and nonprofit organizations) to make decisions. A combined qualitative and quantitative methodological approach was used to evaluate the application's usability and user experience, and results affirmed the ability of the factors of utility, usefulness, and a positive user experience of the residential solar energy adoption of spatial decision support system (RSEA-SDSS). RSEA-SDSS in improving the decision-making process for potential various stakeholders, in utility, solar installations, policy making, and non-profit renewable energy domains.

• Journal of Information Science Theory and Practice
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• 제7권4호
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• pp.56-64
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• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.