• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.507-508
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• 2001

Power transactions are considered as noncooperative game in that participants compete each other to win the bidding game, and as cooperative game in that they have to cooperate to apply the result of bidding game to the physically interconnected power system. This paper applies both noncooperative and cooperative game theories in analyzing the entire process of power transaction.

• ETRI Journal
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• v.34 no.5
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• pp.763-766
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• 2012

This letter proposes an iterative multimode precoding scheme with limited feedback for nonreciprocal MIMO interference channels. Based on analysis of game theory, we model the iterative multimode precoding as a noncooperative game with a finite set of strategies. Numerical results are presented to verify the sum rate performance of the proposed scheme.

• Journal of the Korean Operations Research and Management Science Society
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• v.15 no.2
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• pp.71-83
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• 1990

This paper concerns the analyses of dynamic adjustments in noncooperative games where the market informations are given at discrete time intervals. During the game period, the market informations are given at discrete time intervals. During the game period, the inventories initially stored by players are to be released one day based to the completely competitive market so as to maximize each player's revenue, where players' parameters are unknown one another. Game results have shown that the continuous dynamic adjustment does not necessarily assure the better revenue, and if a player thinks that his parameter is underestimated by hig opponent, then he is better overestimate his opponent's parameter.

• ETRI Journal
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• v.43 no.1
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• pp.17-30
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• 2021

At present, multiple input multiple output radars offer accurate target detection and better target parameter estimation with higher resolution in high-speed wireless communication systems. This study focuses primarily on power allocation to improve the performance of radars owing to the sparsity of targets in the spatial velocity domain. First, the radars are clustered using the kernel fuzzy C-means algorithm. Next, cooperative and noncooperative clusters are extracted based on the distance measured using the kernel fuzzy C-means algorithm. The power is allocated to cooperative clusters using the Pareto optimality particle swarm optimization algorithm. In addition, the Nash equilibrium particle swarm optimization algorithm is used for allocating power in the noncooperative clusters. The process of allocating power to cooperative and noncooperative clusters reduces the overall transmission power of the radars. In the experimental section, the proposed method obtained the power consumption of 0.014 to 0.0119 at K = 2, M = 3 and K = 2, M = 3, which is better compared to the existing methodologies-generalized Nash game and cooperative and noncooperative game theory.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.57-59
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• 2001

The restructuring of power industry is still going on all over the world for last several decades. Many kinds of restructuring model has been studied, proposed, and applied. Among those models, power pool is more popular than others. This paper assumes the power pool market structure having competitive generation sector and a new method is presented to build bidding strategy in that market. The utilities participating in the market have the perfect information on their cost and price functions, but they don't know the strategy to be chosen by others. To define one's strategy as a vector, we make utility's cost/price function into discrete step function. An utility knows only his own strategy, so he estimates the other's strategy using stochastic methods. For considering these conditions, we introduce the Bayesian rules and noncooperative game theory concepts. Also additional assumptions are included for simplification of solving process. Each utility builds the strategy to maximize his own expected profit function using noncooperative Bayesian game. A numerical example is given in case study to show essential features of this approach.

• ETRI Journal
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• v.31 no.1
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• pp.89-91
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• 2009

This letter considers the problem of resource sharing among a relay and multiple user nodes in cooperative transmission networks. We formulate this problem as a sellers' market competition and use a noncooperative game to jointly consider the benefits of the relay and the users. We also develop a distributed algorithm to search the Nash equilibrium, the solution of the game. The convergence of the proposed algorithm is analyzed. Simulation results demonstrate that the proposed game can stimulate cooperative diversity among the selfish user nodes and coordinate resource allocation among the user nodes effectively.

• IE interfaces
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• v.25 no.4
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• pp.431-440
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• 2012

Since pooling is a popular scheme in many areas to attain operational excellence, many researchers investigated the performance of pooling systems. However, rare research could be found on pooling with game situation which has much applicability to real world phenomenon. We analyze the performance of noncooperative pooling system with two servers having different sharing capacity. We investigate the sensitivity of the advantage of capacity pooling on the variation of system parameters, including sharing capacity numbers, pooling probability, pooling strategy and traffic intensity. As a result, we suggest an efficient control policy which facilitate the performance of pooling in a game situation.

• Ocean and Polar Research
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• v.30 no.2
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• pp.173-180
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• 2008

This study demonstrates that cooperative management can provide more benefits than noncooperative management for Korea and Japan fishery. We have studied one management strategy, namely, fishing under joint maximization of net benefits in coastal waters of two countries, using a cooperative game theory. The present net return under non-cooperation amounts to 420,255 million won. However, if two countries cooperate one with another, this figure can get to 2,636,565 million won. We consider this to be an important conclusion as close management relationships have developed between the two countries since the establishment of the EEZ in 1996. The results of the study can also help balance resource conservation and the appropriate catch quota in each country.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.1
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• pp.56-66
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• 2004

As deregulation evolves, pricing electricity becomes a major issue in the electric industry. Participants of competitive marketplace are able to improve their profits substantially by adequately pricing the electricity. In this paper, game theory is applied to analyze the price-clearing in the generation bidding competition and the competition is modeled as the noncooperative and complete information. The result of this analysis can be useful in understanding spot price-clearing of electricity and generating entity's strategic behavior in the competitive electricity market.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.12
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• pp.597-602
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• 2002

The restructuring of power industry is still going on all over the world for last several decades. Many kinds of restructuring model have been studied, proposed, and applied. Among those models, power pool is more popular than other. This paper assumes the power pool market structure having competitive generation sector, and a new method is presented to build a bidding strategy in that market. The utilities participating in the market have the perfect information of their cost and price functions, but they don't know which strategy to be chosen by others. To define one's strategy as a vector, we make utility's cost/price functions into discrete step functions. An utility knows only his own strategy, so he estimates the other's cost/price functions into discrete step functions. An utility knows only his own strategy, so he estimates the other's strategy using Nash equilibrium or stochastic methods. And he also has to forecast the system demand. According to this forecasting result, his payoffs can be changed. Considering these all conditions, we formulate a bidding game problem and apply noncooperative game theory to that problem for the optimal strategy or solution. Some restrictive assumption are added for simplification of solving process. A numerical example is given in Case Study to show essential features and concrete results of this approach.