• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1610-1616
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• 2013

Recently, district heating and cooling (DHC) systems based on combined cycle generation (CCG) providers are increasing in Korea. Since characteristics of combined heat and power (CHP) generators and heat demands of providers, heat trading between DHC providers based on the economic viewpoint is required; the heat trading has been doing. In this paper, a mathematical model for optimal operation based on heat trading between DHC providers is proposed. Especially, start-up characteristic of CCG is included. The operation model is established by mixed integer linear programming (MILP).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.123-129
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• 2013

The aim of this study is to design an intelligent pattern-based real-time trading system (PRTS) using rough set analysis of technical indicators, dynamic time warping (DTW), and genetic algorithm in stock futures market. Rough set is well known as a data-mining tool for extracting trading rules from huge data sets such as real-time data sets, and a technical indicator is used for the construction of the data sets. To measure similarity of patterns, DTW is used over a given period. Through an empirical study, we identify the ideal performances that were profitable in various market conditions.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.295-308
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• 2014

Global trading is an intrinsically complex endeavor with a number of parties involved. World-trading related international organizations have suggested that Single Window (SW) be used as a means to make the trading process simpler and smoother. However, since each firm has its own requirements and objectives with SW, yet there is no consensus as to what traits of 'good' Single Window are. This study uses IT appropriateness as a determinant to explain an impact on information systems success. Historically, IS success was understood as multi-dimensional constructs such as use and performance. In this study we propose another dimension, continuance, and investigate the relationships among these outcome constructs.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.931-934
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• 2005

This paper describes an adaptive recommendation system that provides real-time personalized trading advice to the investors based on their profiles and trading information environment. A proposed system integrates Stochastic technical analysis and artificial neural network that incorporates an adaptive user modeling. The user model is constructed and updated based on initial user profile and recorded user interactions with the system. The information presented to each individual user is also tailor-made to fit the user's behavior and preference. A system prototype was implemented in JAVA. Experiments used to evaluate the system's performance were done on both human subjects and synthetic users. The results show our proposed system is able to rapidly learn to provide appropriate advice to different types of users.

• Journal of Information Technology Applications and Management
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• v.23 no.4
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• pp.25-39
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• 2016

Asset prices decline sharply and stock markets collapse when financial crisis happens. Recently we have encountered more frequent financial crises than ever. 1998 currency crisis and 2008 global financial crisis triggered academic researches on early warning systems that aim to detect the symptom of financial crisis in advance. This study proposes a risk recovery index for detection of good opportunities from financial market instability. We use SVM classifier algorithms to separate recovery period from unstable financial market data. Input variables are KOSPI index and V-KOSPI200 index. Our SVM algorithms show highly accurate forecasting results on testing data as well as training data. Risk recovery index is derived from our SVM-trained outputs. We develop a trading system that utilizes the suggested risk recovery index. The trading result records very high profit, that is, its annual return runs to 121%.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.359-360
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• 2019

This paper proposes partial sharing and trading of digital content as a method of sharing blockchain idurium-based digital content. The platform has three characteristics and aims to improve the existing digital content sales platform. First, it increases the efficiency of sharing and trading through partial sharing and trading systems of digital content. Second, it will be built in the form of blockchain idurium-based smart contracts to ensure the accuracy of transactions. Third, it is possible to analyze the form factor of the comments by improving the grading system.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.281-286
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• 2019

The study aims to analyze the adaptation strategies and resilience of tobacco farmers to face unfavorable trading system. The research method refers to a qualitative approach with phenomenological models and case studies. The findings revealed tobacco farmers in Jember developed various adaptation strategies and resilience through farmer group organizations, partnerships, self-capacity building and access to financial institutions based on economic, social, cultural, and experience values from various sources and interactions among fellow tobacco farmers. The tobacco trading system, which is left to the market mechanism, results in low bargaining power of farmers, this encourages tobacco farmers to develop various adaptation and survival strategies, namely through collective activities of farmer groups, partnerships and self-development and access to financial institutions. Dealing with the unfavorable tobacco trading system, tobacco farmers do not switch to other commodity farming but adapt and make Jember a center for tobacco production in East Java and Indonesia. From this findings, it suggests to the government as the regulator does not only provide subsidies for tobacco farmers, but also must provide various technical assistance to increase the ability of tobacco farmers. More importantly, regulations must be made benefit tobacco farmers other than corporations so that equality can be enjoyed by tobacco economy players.

• The Journal of Fisheries Business Administration
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• v.51 no.4
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• pp.137-146
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• 2020

In this study, the differences of institutional development processes of fishery products wholesale markets were compared between Korea and Japan in order to suggest improvement direction of trading system in Korea. The wholesale markets have shrunk while wholesale and distribution has been becoming larger in size in both countries. A summary of differences in the wholesale market trading systems between Korea and Japan is as follows: first, middle wholesalers play pivotal roles in wholesale transaction in Korea, and wholesale corporations take such roles in Japan. Second, most wholesale corporations take charge of listing in Korea whereas such corporations are in charge of buying in Japan. Third, Korea has high proportion of auction for transactions, in contrast to Japan with high proportion of relative transactions. Forth, Korea maintains more sales within the wholesale markers and has more small and medium customers than Japan. Finally, Korea investigates inside causes to find solutions for the decreased competitive power of the wholesale market, whereas Japan copes with the problem by searching for outside customers. To seek solutions for the decreased competitiveness of Korean fishery products wholesale markets, middle wholesalers' consignment should be limitedly allowed, and improvement direction of wholesale corporations should be investigated in the future study.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.163-171
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• 2021

In this paper, the energy transaction system was optimized by applying a resource allocation algorithm and deep reinforcement learning in the distributed power system. The power demand and supply environment were predicted by deep reinforcement learning. We propose a system that pursues common interests in power trading and increases the efficiency of long-term power transactions in the paradigm shift from conventional centralized to distributed power systems in the power trading system. For a realistic energy simulation model and environment, we construct the energy market by learning weather and monthly patterns adding Gaussian noise. In simulation results, we confirm that the proposed power trading systems are cooperative with each other, seek common interests, and increase profits in the prolonged energy transaction.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.6
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• pp.562-576
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• 2013

Power TAC (Power Trading Agent Competition) is an agent-based simulation for competitions between electricity brokering agents on the smart grid. To win the competition, agents obtain electricity from the electricity wholesale market among the power plants. In this operation, a key to success is balancing the demand of the customer and the supply from the plants because any imbalance results in a significant penalty to the brokering agent. Given the bidding on the wholesale market requires the price and the quantity on the electricity, this paper proposes four different price estimation strategies: exponentially moving average, linear regression, fuzzy logic, and support vector regression. Our evaluations with the competition simulation show which strategy is better than which, and which strategy wins in the free-for-all situations. This result is a crucial component in designing an electricity brokering agent in both Power TAC and the real world.