• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.1-8
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• 2014

Cloud computing helps big data processing to make various information using IT resources. The government has to start the RPS(Renewable Portfolio Standard) and induce the production of electricity using renewable energy equipment. And the government manages system to gather big data that is distributed geographically. The companies can purchase the REC(Renewable Energy Certificate) to other electricity generation companies to fill shortage among their duty from the system. Because of the RPS use voluntary competitive market in REC trade and the prices have the large variation, RPS is necessary to predict the equitable REC price using RPS big data. This paper proposed REC price prediction method base on fuzzy logic using the price trend and trading condition infra in REC market, that is modeled in cloud computing environment. Cloud computing helps to analyze correlation and variables that act on REC price within RPS big data and the analysis can be predict REC price by simulation. Fuzzy logic presents balanced REC average trading prices using the trading quantity and price. The model presents REC average trading price using the trading quantity and price and the method helps induce well-converged price in the long run in cloud computing environment.

• KIEAE Journal
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• v.10 no.4
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• pp.131-136
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• 2010

Because energy consumption of the construction part is very high, there is a growing need to introduce environment-friendly buildings. Therefore Green Building Rating System is enacted in Korea. Though environment-friendly factors such as green area affect the apartment housing price, there's no saying whether Green Building Rating System directly affect the apartment housing price. The purpose of this paper is to estimate the impact of Green Building Rating System on an apartment housing price. The analysis result demonstrated that Green Building Rating System don't affect the apartment housing price. This result means that there is a problem with the effectiveness of Green Building Rating System. The government ought to institute incentive program to ctivate the market of environment-friendly building.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.1
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• pp.43-50
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• 2005

The presence of transmission congestion may reduce the market size and split the bulk power system into smaller systems. Consequently, this can be a key factor to the increase in market price. This paper analyzes the effect of exercising local market power on the market price, and derives a range of indices which quantify the degree and incentive of local market power through statistical analysis in an electricity market with uniform pricing scheme. The applicability and effectiveness of the derived indices on competitive electricity markets are demonstrated on the Korea electricity market.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.763-765
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• 2005

LMP based pricing system has many merits over SMP. One of them is that network congestion can be managed by the market price together with congestion revenue rights. Korean power system has a peculiar property that the transmission line where network congestion occurs is known and does not vary. For such a system, zonal pricing method is considered to be appropriate as it is simpler than nodal pricing. In this paper, we did feasibility study on zone grouping method and tendency of zonal price compared with nodal price.

• Journal of Korea Port Economic Association
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• v.33 no.1
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• pp.75-87
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• 2017

The purpose of this study is to utilize the system dynamics to carry out a medium and long-term forecasting analysis of the bunker price. In order to secure accurate bunker price forecast, a quantitative analysis was established based on the casual loop diagram between various variables that affects bunker price. Based on various configuration variables such as crude oil price which affects crude oil consumption & production, GDP and exchange rate which influences economic changes and freight rate which is decided by supply and demand in shipping and logistic market were used in accordance with System Dynamics to forecast bunker price and then objectivity was verified through MAPEs. Based on the result of this study, bunker price is expected to rise until 2029 compared to 2016 but it will not be near the surge sighted in 2012. This study holds value in two ways. First, it supports shipping companies to efficiently manage its fleet, offering comprehensive bunker price risk management by presenting structural relationship between various variables affecting bunker price. Second, rational result derived from bunker price forecast by utilizing dynamic casual loop between various variables.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.255-263
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• 2003

A multi-agent system designed to represent newly deregulated electricity markets in the USA is aimed at testing the capability of the multi-agent model to replicate the observed price behavior in the wholesale market and developing a smart business intelligence which quickly searches the optimum offer strategy responding to the change in market environments. Simulation results show that the optimum offer strategy is to withhold expensive generating units and submit relatively low offers when demand is low, regardless of firm size; the optimum offer strategy during a period of high demand is either to withhold capacity or speculate for a large firm, while it is to be a price taker a small firm: all in all, the offer pattern observed in the market is close to the optimum strategy. From the firm's perspective, the demand-side participation as well as the intense competition dramatically reduces the chance of high excess profit.

• Journal of the Korea Institute of Building Construction
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• v.15 no.4
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• pp.397-404
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• 2015

Construction equipment cost is critical to estimate the total construction costs, particularly in large and complicated projects. Public construction projects are typically estimated using the Poom-Saem which includes hourly rates for workers and equipments. Despite its importance, the construction equipment cost may not properly reflect the current market value because it is being updated every six years at most. To keep the data for construction equipment cost estimation up to date, it is highly recommended to use the standard market price that is reported each year by the Ministry of Security and Public Administration (MOSPA). However, there is still a wide gap to directly adopt the standard market price for updating the construction equipment prices. Therefore, this paper suggests an effective way to develop an ordinary management systems for updating construction equipment prices in the Poom-saem based on the standard market price.

• Journal of Information Processing Systems
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• v.20 no.1
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• pp.76-84
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• 2024

This study constructed a VAR model with cotton futures and spot price data from April 30, 2009 to November 16, 2022, for empirical analysis utilizing the Granger causality test to analyze the dynamic relationship between cotton futures and spot market prices in China. The impulse response function and variance decomposition analysis showed that the cotton spot prices at flowering have a causal relationship with each other; in terms of mutual influence and impact, futures prices are higher than spot prices. Finally, it proposed countermeasures and suggestions from the perspective of establishing a standardized cotton spot market, improving the laws and regulations of the cotton futures market and trading system, and optimizing the structure of investment subjects.

• The Journal of Fisheries Business Administration
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• v.32 no.2
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• pp.73-89
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• 2001

The market conditions of sea mustard is changing by overproduction, decreasing price, Import of blanched and salted sea mustard from China into Korea domestic market and increasing market share of sea mustard of China in Japan. In addition, the price support program in sea mustard aquaculture must be modified due to the restriction of domestic support by international organization such as WTO. There are two ways to solve those problems. First is that finding a way to solve the overproduction of sea mustard. One of possible ways is the production adjustment by Marketing Order. Second is that finding an alternative way to replace price support program. The possible way is Direct Payment instead of purchase stockpile system. To introduce marketing Order, outlook center, organization of self-management, production adjustment through output control measure, improvement of market structure, and education/publicity arc necessary. Also, to implement marketing order, setting a model business by government is required. There are two steps for implementation of marketing order. First step is to construct Order Committee including organization of producer, people related marketing. However, this committee must run by government for certain short-term. Second step is to improve quality of product and acceleration of demand. At visual point that enforcement of the first step is completed, government has process that government transfers Order Committees self-correcting. It is desirable that government only conduct the support acts such as quality improvement and acceleration of demand. Also, at early stage it is necessary to have aid system for marketing order For example, we can expect that income increase by production adjustment in long run. However, in short run the income of producer may decrease so, it is required to compensate his economic lose. For compensation, The useful means that can be utilized is direct payment. Direct payment is not continued policy. Also, when production adjustment policy such as Marketing Order has effective results, Direct Payment as an assistant measure must be reduced or abolished. Therefore, when production adjustment acts as an effective tool to control overproduction, Direct Payment system.

• Smart Media Journal
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• v.13 no.1
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• pp.9-17
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• 2024

This study aims to develop an integrated agricultural distribution network management system to improve the quality, profit, and decision-making efficiency of agricultural products. We adopt two key techniques: crop maturity detection based on the YOLOX target detection algorithm and market price prediction based on the Prophet model. By training the target detection model, it was possible to accurately identify crops of various maturity stages, thereby optimizing the shipment timing. At the same time, by collecting historical market price data and predicting prices using the Prophet model, we provided reliable price trend information to shipping decision makers. According to the results of the study, it was found that the performance of the model considering the holiday factor was significantly superior to that of the model that did not, proving that the effect of the holiday on the price was strong. The system provides strong tools and decision support to farmers and agricultural distribution managers, helping them make smart decisions during various seasons and holidays. In addition, it is possible to optimize the distribution network of agricultural products and improve the quality and profit of agricultural products.