• 전자공학회논문지 IE
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• v.43 no.4
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• pp.13-20
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• 2006

In the advanced country, It is forecasting farm prices using intelligence style of farming technique. In our country, It is offering basis research to prevent the prices rising and falling, But, It is impossible that no one can predict exactly for farming price. In this paper to improve forecasting farming price using neural network as a preprocessing. Also, we developed a fuzzy algorithm for real time forecasting as a postprocessing about unexpectable conditions. Computer simulation results preyed reducing pricing error which proposed farming price expecting system better than conventional demand forecasting system does not using fuzzy rules.

• Journal of Communications and Networks
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• v.12 no.5
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• pp.449-458
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• 2010

In this paper, we present a distributed resource allocation algorithm for multi-cell uplink systems that increases the weighted sum of the average data rates over the entire network under the average transmit power constraint of each mobile station. For the distributed operation, we arrange each base station (BS) to allocate the resource such that its own utility gets maximized in a noncooperative way. We define the utility such that it incorporates both the weighted sum of the average rates in each cell and the induced interference to other cells, which helps to instigate implicit cooperation among the cells. Since the data rates of different cells are coupled through inter-cell interferences, the resource allocation taken by each BS evolves over iterations. We establish that the resource allocation converges to a unique fixed point under reasonable assumptions. We demonstrate through computer simulations that the proposed algorithm can improve the weighted sum of the average rates substantially without requiring any coordination among the base stations.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.861-863
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• 2005

LMP based congestion management method is suggested as an effective tool, because network congestion can be handled by energy price. It is now being widely used in the North American Electricity Markets. Among them, FGR(Flow-gate rights) is considered to be appropriate for our system, as power flow through the congested line is unidirectional and congestion occurs in the known place. In the CBP market, hedging through transmission right is not necessary even though location pricing system is adopted, because there are no risks in the energy price. Rut, transmission rights should be adopted in the advanced market. Key issue when implementing FGR is how to decide transmission right issuance quantify. This paper deals with a method to decide transmission right issuance quantity by using power. Transfer Distribution Factor(PTDF).

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.97-104
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• 2015

PURPOSES : Expressways experience chronic and recurring congestion, especially during weekends and holidays, because of the increased demands for leisure-related travel. The alternatives to solve chronic and recurring congestion may be three-fold: (1) physical expansion of expressway capacities, (2) road pricing, and (3) temporal and spatial distribution of traffic demands. Among these, the third alternative may be the most cost-effective method for the Korea Expressway Corporation (KEC) that can be achieved by using the existing ITS infrastructure. METHODS : KEC initiated a pilot study in which the traffic on congested expressways was managed by providing traffic condition information (i.e., travel times) of neighboring national highways for taking detours via variable message signs (VMS). This study aimed to estimate the detour rate, and the two pilot studies on Seohaean and Yeongdong expressways yielded many benefits. RESULTS : It was revealed that the total length of congestion segments decreased by 7.8 km, and the average travel speed increased by 5.3 km/h. CONCLUSIONS : Based on these findings, it was concluded that the propagation of detour information via VMSs during congestion hours can help reduce congestion on expressways and increase the benefits of the entire network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3674-3710
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• 2014

In this tutorial, we integrate the concept of cognitive radio technology into game theory and supermarket game theory to address the problem of resource allocation in multiuser multicarrier cognitive radio networks. In addition, multiuser multicarrier transmission technique is chosen as a candidate to study the resource allocation problem via game and supermarket game theory. This tutorial also includes various definitions, scenarios and examples related to (i) game theory (including both non-cooperative and cooperative games), (ii) supermarket game theory (including pricing, auction theory and oligopoly markets), and (iii) resource allocation in multicarrier techniques. Thus, interested readers can better understand the main tools that allow them to model the resource allocation problem in multicarrier networks via game and supermarket game theory. In this tutorial article, we first review the most fundamental concepts and architectures of CRNs and subsequently introduce the concepts of game theory, supermarket game theory and common solution to game models such as the Nash equilibrium and the Nash bargaining solution. Finally, a list of related studies is highlighted and compared in this tutorial.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.5
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• pp.414-424
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• 2015

In this research, we consider a smart grid network of electricity with multiple consumers connected to a monopolistic provider. Each consumer can be informed the real time price changes through the smart meter and updates his consumption schedule to minimize the energy consumption expenditures by which the required power demand should be satisfied under the given real time pricing scheme. This real-time decision making problem has been recently studied through game-theoretic approach. The present paper contributes to the existing literature by incorporating storage appliance into the set of available household appliances which has somewhat distinctive functions compared to other types of appliances and would be regarded to play a significant role in energy consumption scheduling for the future smart grid. We propose a game-theoretic algorithm which could draw the optimal energy consumption scheduling for each household appliances including storage. Results on simulation data showed that the storage contributed to increase the efficiency of energy consumption pattern in the viewpoint of not only individual consumer but also whole system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.437-452
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• 2006

Previous research on two-sided markets has, for the most part, concentrated on indirect network externalities between buyers and sellers. This paper considers direct competition effect among sellers and among buyers as well as indirect network externalities. We develop an analytic model of C2C e-marketplaces and examine whether a monopolistic incumbent could successfully deter new entry into its market. We find that the effect of the number of sellers or buyers on the price of goods depends on whether sellers have decided to sell the goods using an auction or fixed pricing rule and on the characteristics of the goods. We argue that when the effect of the number of sellers on the price of goods is significantly larger than that of buyers, there is a high possibility of entry. In particular, we show that entry becomes more difficult to deter as fixed-price format is adopted more frequently or the proportion of collectables is relatively low.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.158-163
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• 2005

Competitive electricity markets necessitate equitable methods for allocating transmission usage in order to set transmission usage charges and congestion charges in an unbiased and an open-accessed basis. So in competitive markets it is usually necessary to trace the contribution of each participant to line usage, congestion charges and transmission losses, and then to calculate charges based on these contributions. A UPFC offers flexible power system control, and has the powerful advantage of providing, simultaneously and independently, real-time control of voltage, impedance and phase angle, which are the basic power system parameters on which sys-tem performance depends. Therefore, UPFC can be used efficiently and flexibly to optimize line utilization and increase system capability and to enhance transmission stability and dampen system oscillations. In this paper, a mathematical approach to allocate the contributions of system users and UPFCs to transmission system usage is presented. The paper uses a dc-based load flow modeling of UPFC-inserted transmission lines in which the injection model of the UPFC is used. The relationships presented in the paper showed modified distribution factors that modeled impact of utilizing UPFCs on line flows and system usage. The derived relationships show how bus voltage angles are attributed to each of changes in generation, injections of UPFC, and changes in admittance matrix caused by inserting UPFCs in lines. The relationships derived are applied to two test systems. The results illustrate how transmission usage would be affected when UPFC is utilized. The relationships derived can be adopted for the purpose of allocating usage and payments to users of transmission network and owners of UPFCs used in the network. The relationships can be modified or extended for other control devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2709-2734
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• 2020

The growing demand to make wireless data services 5G compatible has necessitated the development of an energy-efficient approach for an effective new wireless environment. In this paper, we first propose a cognitive sensor node (CSN) based game theory for deriving energy via a primary user-transmitted radio frequency signal. Cognitive users' time was segmented into three phases based on a time switching protocol: energy harvest, spectrum sensing and data transmission. The proposed model chooses the optimal energy-harvesting phase as the effected factor. We further propose a distributed energy-harvesting model as a utility function via pricing techniques. The model is a non-cooperative game where players can increase their net benefit in a selfish manner. Here, the price is described as a function pertaining to transmit power, which proves that the proposed energy harvest game includes Nash Equilibrium and is also unique. The best response algorithm is used to achieve the green connection between players. As a result, the results obtained from the proposed model and algorithm show the advantages as well as the effectiveness of the proposed study. Moreover, energy consumption was reduced significantly (12%) compared to the benchmark algorithm because the proposed algorithm succeeded in delivering energy in micro which is much better compared to previous studies. Considering the reduction and improvement in power consumption, we could say the proposed model is suitable for the next wireless environment represented in 5G.

• Journal of Communications and Networks
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• v.13 no.5
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• pp.499-510
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• 2011

Any server offering a routing service in the Internet would naturally be in competition for clients, and clients may need to utilize service from a specific server in order to achieve a desired result. We study the various properties of this competition, such as the fraction of route requests handled by a routing service provider and the fraction of total revenue obtained. As the routing service providers (i.e., servers or routers in this context) compete, they may alter behavior in order to optimize one of the above properties. For example, a service provider may lower the price charged for its service, in order to increase the number of clients served. Our models are based on servers offering a routing service to clients within representative network topologies based on actual Internet sub-graphs. These models provide, a framework for evaluating competition in the Internet. We monitor key aspects of the service, as several variables are introduced into the models. The first variable is the fraction of client requests that will pay more for a better quality route. The remaining requests are normal client requests that are satisfied by the most economical route. The second variable is the fraction of servers who choose to lower service prices in order to maximize the number of client requests served. As this fraction increases, it is more likely that a server will lower the price. Finally, there are some resource constraints applied to the model, to increase the difficulty in providing a routing solution, i.e., to simulate a realistic scenario. We seek to understand the effect on the overall network, as service providers compete. In simple cases, we show that this competition could have a negative impact on the overall efficiency of a service. We show that the routing variety present in the larger models is unable to mask this tendency and the routing service performance is decreased due to competition.