• Title/Summary/Keyword: Network theory

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Expert System for Fault Diagnosis of Transformer

  • Kim, Jae-Chul;Jeon, Hee-Jong;Kong, Seong-Gon;Yoon, Yong-Han;Choi, Do-Hyuk;Jeon, Young-Jae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.7 no.1
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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.

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A Study on Mix Design Model of High Strength Concrete using Neural Networks (신경망을 이용한 고강도 콘크리트 배합설계모델에 관한 연구)

  • Lee, Yu-Jin;Lee, Sun-Kwan;Kim, Yeong-Soo
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2012.11a
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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.

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Survey on IEEE 802.11 DCF Game Theoretic Approaches (IEEE 802.11 DCF에서의 게임 이론적 접근방법 소개)

  • Choi, Byeong-Cheol;Kim, Jung-Nyeo;Ryu, Jae-Cheol
    • Proceedings of the KIEE Conference
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    • 2007.04a
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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.

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Extensions of Knowledge-Based Artificial Neural Networks for the Theory Refinements (영역이론정련을 위한 지식기반신경망의 확장)

  • Shim, Dong-Hee
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.38 no.6
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    • pp.18-25
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    • 2001
  • KBANN (knowledge-based artificial neural network) combining the analytical learning and the inductive learning has been shown to be more effective than other machine learning models. However KBANN doesn't have the theory refinement ability because the topology of network can't be altered dynamically. Although TopGen was proposed to extend the ability of KABNN in this respect, it also had some defects. The algorithms which could solve this TopGen's defects, enabling the refinement of theory, by extending KBANN, are designed.

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Game Theory-Based Scheme for Optimizing Energy and Latency in LEO Satellite-Multi-access Edge Computing

  • Ducsun Lim;Dongkyun Lim
    • International journal of advanced smart convergence
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    • v.13 no.2
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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.

The Effect of Social Network Service on Social Capital (소셜 네트워크 서비스가 사회적 자본에 미치는 영향)

  • Kim, Jong-Ki;Kim, Jin-Sung;Lei, Zheng-Jie
    • The Journal of Information Systems
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    • v.21 no.3
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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.

Social Network Games (SNG) to concentrate on the analysis of causes (소셜네트워크 게임(SNG)에 몰입하는 원인 분석 연구)

  • Kim, Tae-Gyu;Ryu, Seuc-Ho;Kyung, Byung-Pyo;Lee, Wan-Bok
    • Journal of Digital Convergence
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    • v.10 no.1
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    • pp.445-453
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    • 2012
  • With the development of recent gaming industry in the production side of the game has expressed concern about. To avoid such generalizations about the diversification of the game for any effort is required. As an aspect of the game is that social networks are emerging. In particular, the element of commitment to targeting the public should not be in game development is an important factor in the liver. In this study, the analysis of previous studies on flow and Raph Koster fun theory is based on the theory extracted from the social network game cause flow through the case study is presented.

Optimal Network Defense Strategy Selection Based on Markov Bayesian Game

  • Wang, Zengguang;Lu, Yu;Li, Xi;Nie, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.11
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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.

Priority Decision Making for Planning A Long-term Sustainable High-speed Rail Network using Multi-Attribute Utility Theory (지속가능한 고속철도망 계획을 위한 투자우선순위 선정에 관한 연구 : 다원-속성 효용이론을 이용하여)

  • Park, Jin-Kyung;Eom, Jin-Ki;Lee, Jun
    • Journal of the Korean Society for Railway
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    • v.11 no.1
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    • pp.45-53
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    • 2008
  • With the growing international consensus regarding sustainable development of transportation, the plan of transportation infrastructure needs to meet various requirements toward enhancing environmental conditions. Accordingly, the upcoming long-term plan of high-speed rail network has to be reflecting the sustainability of transportation systems. In this paper, we demonstrate an application of methodologies based on multi-attribute utility theory for determining priorities of sustainable high-speed rail investment. The proposed methodologies identify indicators for sustainable transportation systems such as economic, environmental, and social ones and then, evaluate priority for planning a long-term sustainable high-speed rail network by comparing the relative importance among indicators. This will help transportation agencies to prioritize high-speed rail investment toward sustainable transportation systems.

A trend analysis of the Knowledge Management Research using graph theory and network model (그래프 이론 및 네트워크 모델을 이용한 지식경영연구 논문 트랜드 분석)

  • Lee, Dong Hyun;Lee, Ho;Kim, Jungmin
    • Knowledge Management Research
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    • v.17 no.1
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    • pp.1-16
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    • 2016
  • The purpose of this study is to analyze 352 scholarly journals and 1496 keywords in Knowledge Management Research from 2000 to 2015 and provide systematical view point of research trend in the area of knowledge management using graph theory and network model. The relational patterns among keywords as well as keywords which recently received noticeable attention and keywords which receded from the spotlight in recent years in the knowledge management literature were identified. The result of this study can be used as a foundation of future research ideas in knowledge management.