• 한국지능시스템학회논문지
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• 제7권1호
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• pp.45-53
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• 1997

This paper presents hybrid expert system for diagnosis of electric power transformer faults. The expert system diagnose and detect faults in oil-filled power transformers based on dissolved gas analysis. As the preprocessing stage, fuzzy information theory is used to manage the uncertainty in transformer fault diagnosis using dissolved gas analysis. The Kohonen neural network takes the interim results by applying fuzzy informations theory as inputs, and performs the transformer fault diagnosis. The Proposed system tested gas records of power transformers from Korea Electric Power Corporation to verify the diagnosis performance of transformer faults.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2012년도 추계 학술논문 발표대회
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• pp.253-254
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• 2012

The purpose of this study is to suggest and verify high-strength concrete mix design model applying neural network theory, in order to minimize effort and time wasted by using trial and error method utill now. There are 7 input and 2 output to predict mix design. 40 data of mix design were learned with back-propagation algorithm. Then they are repeatedly learned back-propagation in neural network theory. Also, to verify predicted model, we analyzed and compared value predicted from 60MPa mix design with value measured by actual compressive strength test.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.240-242
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• 2007

The game theoretic analysis in wireless networks can be classified into the jamming game of the physical layer, the multiple access game of the medium access layer, the forwarder's dilemma and joint packet forwarding game of the network layer, and etc. In this paper, the game theoretic analysis about the multiple access game that selfish nodes exist in the IEEE 802.11 DCF(Distributed Coordination Function) wireless networks is addressed. In this' wireless networks, the modeling of the CSMA/CA protocol based DCF, the utility or payoff function calculation of the game, the system optimization (using optimization theory or convex optimization), and selection of Pareto-optimality and Nash Equilibrium in game strategies are the important elements for analyzing how nodes are operated in the steady state of system. Finally, the main issues about the game theory in the wireless network are introduced.

• 전자공학회논문지CI
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• 제38권6호
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• pp.18-25
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• 2001

분석적학습과 귀납적학습을 결합한 지식기반신경망은 다른 기계학습모델보다 우수한 성능을 나타내고 있다. 그러나 지식기반신경망에서는 신경망이 형성된 후 그 구조를 동적으로 변경할 수 없어서 영역이론정련화 기능을 제공하지 못한다. 이러한 단점을 갖고 있는 지식기반신경망을 보완하기 위하여 TopGen 알고리즘이 제안되었지만 부분적인 문제점을 안고 있다. 본 논문에서는 TopGen의 문제점을 해소하면서 지식기반 신경망을 확장하여 영역이론정련기능을 부여하는 방안 2가지를 제시하고 이를 평가하였다.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.7-15
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• 2024

6G network technology represents the next generation of communications, supporting high-speed connectivity, ultra-low latency, and integration with cutting-edge technologies, such as the Internet of Things (IoT), virtual reality, and autonomous vehicles. These advancements promise to drive transformative changes in digital society. However, as technology progresses, the demand for efficient data transmission and energy management between smart devices and network equipment also intensifies. A significant challenge within 6G networks is the optimization of interactions between satellites and smart devices. This study addresses this issue by introducing a new game theory-based technique aimed at minimizing system-wide energy consumption and latency. The proposed technique reduces the processing load on smart devices and optimizes the offloading decision ratio to effectively utilize the resources of Low-Earth Orbit (LEO) satellites. Simulation results demonstrate that the proposed technique achieves a 30% reduction in energy consumption and a 40% improvement in latency compared to existing methods, thereby significantly enhancing performance.

• 한국정보시스템학회지:정보시스템연구
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• 제21권3호
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• pp.163-186
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• 2012

With the development of Internet and transition to information society, social capital is expanding to online from the traditional offline context. Especially with the widespread of social network service(SNS) the number of SNS users is increasing sharply and the importance of online social capital has been more and more significant. Most studies on social capital focused on organizational aspects but few studies have payed attention to personal aspect. Empirical studies on the relation between SNS and social capital were seldom conducted in previous studies. Based on the theory of social capital this study targets on the relationship formed through SNS and analyzes on how the relationship affects the perceived social capital. In this study 'self-presentation', 'playfulness' and 'critical mass' are posited as the antecedent factors of 'SNS usage'. This study proposes a research model to examine the effect of 'SNS usage' on 'relationship reinforcement', 'relationship building' and 'perceived social capital'. According to the results of empirical analysis, 'self-presentation', 'playfulness' and 'critical mass' can generate significant positive influence on 'SNS usage'. It also confirms not only the effect of 'relationship reinforcement' and 'relationship building' formed through SNS on 'perceived social capital' but also relationship between the social capital formation and SNS usage. The outcome obtained in this study can be applied in developing SNS services.

• 디지털융복합연구
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• 제10권1호
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• pp.445-453
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• 2012

최근 게임산업의 발전과 더불어 한편에서는 게임의 부작용에 대해서 우려를 표하고 있다. 이에 대한 일반화를 방지하기 위해서라도 게임의 다양화에 대한 노력은 필요하다. 그 일면으로 소셜네트워크 게임이라는 것이 대두되고 있다. 특히 몰입이라는 요소는 대중을 대상으로 하는 게임 개발에서는 간과에서는 안 될 중요한 요소이다. 본 연구에서는 몰입에 관한 기존 연구를 분석하고 라프코스터의 재미이론을 통해 추출된 요인을 기반으로 소셜네트워크 게임 사례분석을 통해 몰입 원인을 제시하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5631-5652
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• 2019

The existing defense strategy selection methods based on game theory basically select the optimal defense strategy in the form of mixed strategy. However, it is hard for network managers to understand and implement the defense strategy in this way. To address this problem, we constructed the incomplete information stochastic game model for the dynamic analysis to predict multi-stage attack-defense process by combining Bayesian game theory and the Markov decision-making method. In addition, the payoffs are quantified from the impact value of attack-defense actions. Based on previous statements, we designed an optimal defense strategy selection method. The optimal defense strategy is selected, which regards defense effectiveness as the criterion. The proposed method is feasibly verified via a representative experiment. Compared to the classical strategy selection methods based on the game theory, the proposed method can select the optimal strategy of the multi-stage attack-defense process in the form of pure strategy, which has been proved more operable than the compared ones.

• 한국철도학회논문집
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• 제11권1호
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• pp.45-53
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• 2008

본 연구는 중장기적 고속철도망 계획을 위한 투자우선순위를 전통적인 평가기법에서 벗어나 지속가능 한 교통의 관점에서 이를 분석할 수 있는 방법론을 제안하고, 다원-개준 의사결정기법 중의 하나인 다원-속성 효용이론(MAUT)을 이용하여 이를 분석하였다. 지속가능 한 교통지표는 경제지표, 사회지표 및 환경지표로 구분하였으며, 지속가능 한 고속철도망 지수 분석 결과 경부와 호남 고속철도 이후에 건설되어야 할 우리나라의 고속철도망 노선축의 투자우선순위는 동서축, 남해축, 서해축 등의 순서로 분석되었다.

• 지식경영연구
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• 제17권1호
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• pp.1-16
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• 2016

본 연구에서는 국내 지식경영 분야의 연구동향들이 어떻게 전개되어 왔는지 살펴보기 위해 한국지식경영학회의 지식경영연구 학술지에 2000년 부터 2015년까지 게재된 총 352개의 논문의 1496개의 키워드를 대상으로 그래프 이론 및 네트워크 모델을 이용하여 추세를 분석하였다. 분석 결과를 통하여 최근 각광받고 키워드들, 네트워크의 중심에서 멀어진 키워드들, 그리고 키워드들 간의 단절고리에 대하여 알아보았다. 연구자들은 본 연구결과를 활용하여 향후 지식경영 분야 후속연구의 설계 및 주제선정을 위한 기초자료로 삼을 수 있을 것이다.