• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.133-141
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• 1994

Conventional competitive learning algorithms compute the Euclidien distance to determine the winner neuron out of all predetermined output neurons. In such cases, there is a drawback that the performence of the learning algorithm depends on the initial reference(=weight) vectors. In this paper, we propose a new competitive learning algorithm that dynamically generates output neurons. The proposed method generates output neurons by dynamically changing the class thresholds for all output neurons. We compute the similarity between the input vector and the reference vector of each output neuron generated. If the two are similar, the reference vector is adjusted to make it still more like the input vector. Otherwise, the input vector is designated as the reference vector of a new outputneuron. Since the reference vectors of output neurons are dynamically assigned according to input pattern distribution, the proposed method gets around the phenomenon that learning is early determined due to redundant output neurons. Experiments using speech data have shown the proposed method to be superior to existint methods.

• Journal of information and communication convergence engineering
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• v.3 no.2
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• pp.101-104
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• 2005

Recently advanced countries are making every effort to promote the efficiency of electric power production and supply, to deal with the environmental problems, and to develop the new energy. In particular, they are driving forward to develop various technologies for electric power in mid-long term, that are technology for building infrastructure of power transportation, establishing service network for account management using electronic technologies, elevating economic productivity by innovative electronic technologies, control-ling the discharge of global warming gas, using clean efficient energy, and so forth. However, power technology of Korea lagged behind than technology of advanced countries. Also, resources for developing power technology are limited in our country. Therefore, it is necessary to improve the efficiency of R&D investment. For it, our country must compare and analyze with technologies of advanced countries which are taking competitive advantage in the main future energy. Through comparative analysis, limited R&D resources of our country must be concentrated on technologies that can secure competitive advantage from now on.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.45-50
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• 2020

A Language model with neural networks commonly trained with likelihood loss. Such that the model can learn the sequence of human text. State-of-the-art results achieved in various language generation tasks, e.g., text summarization, dialogue response generation, and text generation, by utilizing the language model's next token output probabilities. Monotonous and boring outputs are a well-known problem of this model, yet only a few solutions proposed to address this problem. Several decoding techniques proposed to suppress repetitive tokens. Unlikelihood training approached this problem by penalizing candidate tokens probabilities if the tokens already seen in previous steps. While the method successfully showed a less repetitive generated token, the method has a large memory consumption because of the training need a big vocabulary size. We effectively reduced memory footprint by encoding words as sequences of subword units. Finally, we report competitive results with token level unlikelihood training in several automatic evaluations compared to the previous work.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.6
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• pp.340-346
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• 2003

This paper presents a game theory application for an analysis of uniform price auction in a simplified competitive electricity market and analyzes the properties of Nash equilibrium for various conditions. We have assumed that each generation firm submits his bid to a market in the form of a sealed bid and the market is operated as a uniform price auction. Two firms are supposed to be the players of the market, and we consider the maximum generation quantity constraint of one firm only. The system demand is assumed to have a linear relationship with market clearing prices and the bidding curve of each firm, representing the price at which he has a willingness to sell his generation quantity, is also assumed to have a linear function. In this paper, we analyze the effects of maximum generation quantity constraints on the Nash equilibrium of the uniform price auction. A simple numerical example with two generation firms is demonstrated to show the basic idea of the proposed methodology.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.44-47
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• 2001

In a competitive environment of electric power industy, the level of uncertainty increase due to generation investment decisions creating new challenge to transmission system planner. The use of a locational signal and the provision of a indicative plan to control the generation investment reasonably is very important in the viewpoint of a regulator. The main target of this stuty is to emphasize on the necessity for considering simultaneously both generation and transmission expansion plan. This paper demonstrate the many case studies to make certain of the necessity for the interconnection between generation and transmission planning. In addition to, the planning in Korea power industry is considerd.

• IE interfaces
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• v.14 no.1
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• pp.54-58
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• 2001

In this study, we suggest a multi-generation Lotka-Volterra model, which is a competition model using game theory and complex system theory. The suggested model shows many improvements to weakness of a well known Bass model to forecast new technology in competitive markets. We show that the Lotka-Volterra model has strong power to forecast mobile communication services when it is used for competition of 1st generation mobile phone service and 2nd generation phone service in Korea. We finally use the model to forecast IMT-2000 service, the 3rd generation mobile communication service.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.675-685
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• 2013

Generation capacities and transmission line constraints in a competitive electricity market make it troublesome to compute Nash Equilibrium (NE) for analyzing participants' strategic generation quantities. The NE can cause a mixed strategy NE rather than a pure strategy NE resulting in a more complicated computation of NE, especially in a multiplayer game. A two-level hierarchical optimization problem is used to model competition among multiple participants. There are difficulties in using a mathematical programming approach to solve a mixed strategy NE. This paper presents heuristics applied to the mathematical programming method for dealing with the constraints on generation capacities and transmission line flows. A new formulation based on the heuristics is provided with a set of linear and nonlinear equations, and an algorithm is suggested for using the heuristics and the newly-formulated equations.

• Korean System Dynamics Review
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• v.4 no.1
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• pp.33-53
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• 2003

How to maintain the optimal electric power generation mix is one of the important problems in electric power industry. The objective of this study is to develop a computer model which can be used to forecast the investment in power generation unit by the plant owners after restructuring of electric power industry. Restructuring of electric power industry will make difference in decision making process of investment in power generation unit. After Privatiazation of Power Industry, Gencos will think that profit is the most important factor among all others attracting the investment in the industry. Coal power generation is better than LNG CCGT in terms of profit. However, many studies show that LNG CCGT will be main electric power generation source because the rest of factors other than profit in LNG CCGT are superior than Coal power generation. Because the nst of factors other than profit in LNG CCGT are superior than Coal power generation. The impacts of the various government policies can be analyzed using the computer model, thus the government can formulate effective policies for achieving the desired electric power generation mix.

• IE interfaces
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• v.17 no.3
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• pp.269-281
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• 2004

How to maintain the optimal electric power generation mix is one of the important problems in electric power industry. The objective of this study is to develop a computer model which can be used to forecast the investment in power generation unit by the plant owners after restructuring of electric power industry. Restructuring of electric power industry will make difference in decision making process of investment in power generation unit. After Privatiazation of Power Industry, Gencos will think that profit is the most important factor among all others attracting the investment in the industry. Coal power generation is better than LNG CCGT in terms of profit. However, many studies show that LNG CCGT will be main electric power generation source because the rest of factors other than profit in LNG CCGT are superior than Coal power generation. The impacts of the various government policies can be analyzed using the computer model, thus the government can formulate effective policies for achieving the desired electric power generation mix.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.9
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• pp.542-549
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• 2003

In this paper, a novel approach to generator maintenance scheduling strategy in competitive electricity markets based on non-cooperative dynamic game theory is presented. The main contribution of this study can be considered to develop a game-theoretic framework for analyzing strategic behaviors of generating companies (Gencos) from the standpoints of the generator maintenance-scheduling problem (GMP) game. To obtain the equilibrium solution for the GMP game, the GMP problem is formulated as a dynamic non-cooperative game with complete information. In the proposed game, the players correspond to the profit-maximizing individual Gencos, and the payoff of each player is defined as the profits from the energy market. The optimal maintenance schedule is defined by subgame perfect equilibrium of the game. Numerical results for two-Genco system by both proposed method and conventional one are used to demonstrate that 1) the proposed framework can be successfully applied in analyzing the strategic behaviors of each Genco in changed markets and 2) both methods show considerably different results in terms of market stability or system reliability. The result indicates that generator maintenance scheduling strategy is one of the crucial strategic decision-makings whereby Gencos can maximize their profits in a competitive market environment.