• Clean Technology
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• v.28 no.2
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• pp.138-146
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• 2022

Electricity has become a factor that dramatically affects the market economy. The day-ahead system marginal price determines electricity prices, and system marginal price forecasting is critical in maintaining energy management systems. There have been several studies using mathematics and machine learning models to forecast the system marginal price, but few studies have been conducted to develop, compare, and analyze various machine learning and deep learning models based on a data-driven framework. Therefore, in this study, different machine learning algorithms (i.e., autoregressive-based models such as the autoregressive integrated moving average model) and deep learning networks (i.e., recurrent neural network-based models such as the long short-term memory and gated recurrent unit model) are considered and integrated evaluation metrics including a forecasting test and information criteria are proposed to discern the optimal forecasting model. A case study of South Korea using long-term time-series system marginal price data from 2016 to 2021 was applied to the developed framework. The results of the study indicate that the autoregressive integrated moving average model (R-squared score: 0.97) and the gated recurrent unit model (R-squared score: 0.94) are appropriate for system marginal price forecasting. This study is expected to contribute significantly to energy management systems and the suggested framework can be explicitly applied for renewable energy networks.

• New & Renewable Energy
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• v.10 no.2
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• pp.40-47
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• 2014

This study is intended to analyze the appropriate scope for 9.9MW biomass cogeneration, feasibility and sensitivity according to changing market situation. In the study, the heat load is classified into three types to predict heat sales and find out the appropriate scope of thermal business that is operated in CHP 34.42 Gcal/h, PLBwg 70 Gcal/h of cogeneration. the feasibility is estimated based on internal rate of return (IRR) and net present value(NPV). the sensitivity is analyzed in terms of biomass fuel cost, unit price of heating cost, investment cost, SMP unit price and REC unit price.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.196-197
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• 2022

This study aims to come up with the revision of construction standard unit price for concrete pavement works to improve its applicability and availability by a construction site survey. Construction site survey was conducted from March to November 2021 with 36 construction sites. This results of the revision are expected to support to public construction project owner or estimator in construction cost estimation works.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.6
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• pp.72-81
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• 2002

The purpose of this study is to determine the impact of the soil load for artificial ground on a building's structural expenses. Three types of soil - 100% soil, soil mixed with 50% perlite, and 100% artificial soil - were used for this study. A one story concrete steel building specific to each soil load was designed, and then, the cost of steel and concrete used for the design was estimated. As the result of this study, the structural expenses in the case of 5:5 mixed soil can be reduced about 17% compare with 100% soil. Using artificial soil, the structural expenses can be cut about 32% compare to 100% soil and about 12% less when 5:5 mixed soil is used. However, considering total expense which includes the structural expense and soil expense, the expense of 5:5 mixed soil have an increase 25% compared with 100% soil. In the artificial soil, the total expense is 45% more expensive than 100% soil and 17% higher when 5:5 mixed soil is used because of the high unit price of artificial soil. This study expected substantial savings in structural cost as the soil-load was lightened. But, savings were significantly reduced because the unit price of the artificial soil is much more expensive than the price of the natural one. Therefore, further research on methods of reducing the unit price of the artificial soil should be conducted in order to extend green space on to artificial ground.

• KIEAE Journal
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• v.7 no.3
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• pp.11-20
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• 2007

The purpose of this study is to analyse the effects of the eco-friendly factors on the apartment housing price rise and to suggest the desirable way of marketing strategy for apartment housing. For the analysis, the data of apartment sites in Seoul had been collected from September 2006 to February 2007. The data consisted of 95 apartment sites in Seoul. Data were analyzed with descriptives, crosstabs, and discriminant analysis by SPSS/PC for Window. Following result was obtained. The eco-friendly apartment housing price rate in Seoul was determined by eco-friendly landscape, green space rate, house unit size, installment sale price per pyeong, floor space index, distance from subway station when it was not considered the impact of building age, construction company's brand, and autonomous districts. Findings of this research can provide valuable information for marketing strategy of housing construction company.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.822-823
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• 2007

It is easily can be expected that Korea cannot be free under the regulation, because Korea is one of the major $CO_2$ emitter in the world. Even though Korea currently doesn't have any obligation to mitigate the carbon emission, power industry needs to study the effect of that. this paper aims to analyze the change of economic loading order for generation dispatch by various carbon price, looking at each plant's or generator's variable generation cost per unit electricity(kWh) that consists of basic generation price calculated by automatic generation system planning model, WASP 4.0, and $CO_2$ price per unit electricity generation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.7
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• pp.97-105
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• 2014

This article examines the causality relationship among SMP, base-load share, LNG import price, and exchange rate in Korean power market during 2002~2012, using unit root test, cointegration test, and vector error correction model(VECM). The cointegration test shows that 4 variables without unit root have been in the long-run causality. As the results of ECM, SMP is analyzed to have been unilaterally caused from LNG import price and base-load share in the shot-run, while it has been unilaterally caused from LNG import price and exchange rate in the long-run. This article has the following policy implications: the adjustment of exchange rate to reduce he risk of LNG import price and the proper securement of base-load share for the long-run stability of SMP.

• International Area Studies Review
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• v.15 no.1
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• pp.219-240
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• 2011

The main purpose of this study is to analyze the effects of stock price and real estate price on the money demand. We investigated the demand for money for 25 money units of 10 countries. To estimate the money demand functions, Johansen's cointegration and ARDL-bounds test were employed. Additionally, Stock and Watson's DOLS method was applied to estimate long-run cointegration vectors. According to the results of cointegration test, stock price and real estate price are crucial in the long-run equilibrium relationship. There were no cointegration relationships among money demand, real income, interest rate, and exchange rate in 12 money unit models. However, by including stock price and real estate price on the tested models, we could find strong cointegration relationships, using ARDL-bounds test. The results of DOLS confirm that stock price and real estate price are effective factors influencing on money demands. Especially, the coefficient of real estate price is statistically significant in the 19 out of 20 money unit models. However, the direction and magnitude of coefficients of asset prices are different across countries and money units.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.589-601
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• 2020

The Construction Standard Unit Price (CSUP) sets the standard for calculating the estimated construction cost. The CSUP is used as basic data for preparing a standard price for public construction. Currently, the CSUP is calculated in consideration of the market and construction field conditions. However, a long-term management plan was established to prepare revised standards. As part of the plan, a field survey was conducted on changes in construction conditions and market prices. However, the plan continued for more than 5 years. Thus, the plan has a problem of difficulty continuously managing primary activities that have high importance and high price volatility. Therefore, to efficiently manage the CSUP, this study identifies the primary activities of the CSUP and presents a management plan. Through importance analysis and unit price volatility analysis, 242 primary activities in 35 activity groups were identified. Also, a management plan is presented based on the importance levels of activities. The primary activities and management plan could enable the timely revision of important activities. The results of this study provide a base for reflecting the appropriateness of construction cost criteria on time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.171-176
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• 2021

This paper deals with bid evaluation problem that chooses the vendors and quantity with minimum purchasing cost for bid information of setup cost and unit price. For this problem, the branch-and-bound(BB) and branch-and-cut(BC) methods are well-known. But these methods can be fail to obtain the optimal solution. This paper gets the initial feasible solution with procuring quantity assignment principle in accordance with the unit price or setup cost rank-first. Then procuring quantity moving optimization(vendor change) is execute take account of unit price or setup cost rank. As a result of experimentation, the propose algorithm is significantly lower compared to BB and BC.