• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.562-563
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• 2008

경쟁적 전력시장에서는 이익주체의 다양화로 송전망확장은 개별 시장참여자의 경제적 편익에 큰 영향을 미칠 수 있다. 송전설비 투자계획은 미래 전력 시장 및 계통의 예측을 바탕으로 하기 때문에 예측의 불확실성에서 발생하는 설비투자의 과잉.과소투자의 최소화 방안이 필요하다. 따라서 본 논문은 송전망확장사업의 경제적 가치를 평가하는 방법에 대해 연구였고 미래 시장 및 계통의 불확실성을 반영하기 위해 전력수요와 연료가격의 과거 예측오차의 표준편차를 이용한 예측값의 확률밀도함수의 모델링 방법을 이용한 송전망확장의 경제성 평가 방법을 제시한다. Monte Carlo Sampling을 이용, 송전망확장으로 인한 시장참여자의 경제적 편익 변화의 기대값과 편익 변화의 범위를 산출함으로써 설비투자의 리스크와 잠재효과에 대해 분석한다.

• Proceedings of the Optical Society of Korea Conference
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• 1991.07a
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• pp.123-128
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• 1991

최근 새로운 렌즈 가공기술들이 개발됨에 따라 종전에는 가공 자체가 불가능하거나 생산에 많은 비용이 들던 광학 소자들이 저렴한 가격으로 생산이 가능하게 되었다. 이 논문에서는 실제 생산에 사용하고 있는 분야에 대해서 논하였다. 또한 장래의 전망에 대해서도 예측해 보았다.

• Digital Contents
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• no.5 s.24
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• pp.56-62
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• 1995

소개된지 10년이라는 짧은 기간 동안, CD-ROM은 정보산업계에 커다란 변화를 몰고 왔다. 예를 들면, CD-ROM은 많은 회사에서 온라인검색을 대체하게 했다. CD-ROM은 이제 막 이룩하려는 단계이며, 미래가 어떨지 예측하기는 어렵다. CD-ROM하드웨어 및 소프트웨어 소비시장의 성장으로, 모든 전문 어플리케이션분야에서도 가격 하락, 첨예한 경쟁, 사양 및 기능의 다양화라는 충격을 줄 것이다. 소비시장의 성장은 전문이용자들에게도 좋은 뉴스가 될 것이다.

• 월간 기계설비
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• s.236
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• pp.94-95
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• 2010

예전에도 본 칼럼에서 한번 소개했지만 변화가 많을 것으로 예측될 경우에 유효한 경영 전략 중의 하나가 시나리오 경영이다. 즉, 미래에 관하여 몇 가지 경우의 수를 상정하고 시뮬레이션을 해본 후 각 상황에 맞는 가상 시나리오를 만드는 것이다. 미국의 쉘 정유사 등이 석유 파동시 큰 효과를 보아 유명해진 전략으로 자재 가격 변동이 심할 것으로 보이는 우리 설비 업계에도 적용해 볼 만하다. 본문에서 구체적으로 살펴보도록 하겠다.

• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.162-170
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• 2006

Neural network analysis is expected to enhance the forecasting ability for the real estate market. This paper reviews definition, structure, strengths and weaknesses of neural network analysis, and verifies the applicability of neural network analysis for the real estate market. Neural network analysis is compared with regression analysis using the same sample data. The analyses model the macroeconomic parameters that influence the sales price of apartments. The results show that neural network analysis provides better forecasting accuracy than regression analysis does, what confirms the applicability of neural network analysis for the real estate market.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.1-13
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• 2002

Estimating the Value-at-Risk (VaR) of a non-listed or newly listed company in stock market is impossible due to lack of stock exchange data. This study employes Case-Based Reasoning (CBR) for estimating VaR's of those companies. CBR enables us to identify and select existing companies that have similar financial and non-financial characteristics to the unlisted target company. The VaR's of those selected companies can give estimates of VaR for the target company. We developed a system called VAS-CBR and showed how well the system estimates the VaR's of unlisted companies.

• Journal of Agricultural Extension & Community Development
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• v.22 no.4
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• pp.423-434
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• 2015

This paper predicts the onion's cultivation areas, yields per unit area, and wholesale prices during ship dates by using wholesale price data from the Korea Agro-Fisheries & Food Trade Corporation, the production data from the Statistics Korea, and the weather data from the Korea Meteorological Administration with an ARDL model. By analyzing the data of wholesale price, rural household income and rural total earnings, onion cultivation areas in 2015 are estimated to be 21,035, 17,774 and 20,557(ha). In addition, onion yields per unit area of South Jeolla Province, North Gyeongsang Province, South Gyeongsang Province, Jeju Island, and the whole country in 2015 are estimated to be 5,980, 6,493, 6,543, 6,614, 6,139 (kg/10a) respectively. By using onion production's predictive value found from onion's cultivation areas and yields per unit area in 2015, the onion's wholesale prices in June are estimated to be 780 won, 1,100 won, and 820 won for each model. Predicted monthly price after the onion's ship dates is analyzed to exceed 1,000 won after August.

• Journal of Korean Society of Forest Science
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• v.88 no.1
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• pp.1-10
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• 1999

The dynamic relationships among import prices of roundwood are analyzed using the time series approach. A vector autoregression(VAR) model is estimated for six import prices(New Zealand, Chile, Russia, U.S.A., PNG, and Malaysia). Then Granger's causality test, variance decomposition analysis, and impulse response function analysis are also conducted. The major results are summarized as follows : (1) The prices of New Zealand and Russia are caused by only own lagged prices. (2) The prices of Chile and PNG are effected by New Zealand, the price of PNG is effected by New Zealand and Russia, and the price of U.S.A. is effected by those of Chile and PNG, respectively. (3) An exogenous shock in New Zealand will affect the prices of New Zealand, PNG, U.S.A., Chile, Russia. (4) An exogenous shock in Chile may also affect the prices of Chile, U.S.A., Russia.

• Environmental and Resource Economics Review
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• v.28 no.1
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• pp.121-145
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• 2019

This paper investigates the relationship between the oil price and the major petroleum products prices at the trading hubs such as Singapore, North West Europe and the US New York Harbor. We focus on the lead-lag relationship between the weekly petroleum prices from 2009 to 2016 based on the vector error correction model. We find that the oil price leads the prices of petroleum products in the long term, while there is bidirectional causality in the short term. On the other hand, prices of petroleum products in regions with high import dependency, such as Europe gas oil and jet fuel price, are exogenous in the long term. We also present evidence that prices of petroleum products in region with a large global-market share lead prices in other regions. However, if the region is in an over-production situation and low industry concentration, it may lose its price leadership due to intense competition. The result in this study can provide a useful information to petroleum refining companies in forecasting fluctuations of product price, and hence in planning their regional arbitrage trading activities.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.137-153
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• 2016

The price of agricultural products has changed from year to year, the m ajor c ause o f price fluctuation is the imbalance of supply and demand. Materials which are mainly used in korean cabbage production volume is the forecast model, using the cadastral result, slope calculation is impossible to achieved. For this reason, this implies the drastic decrease of prices and the prediction of supply and demand of field crops that is cultivated in a highland slope area, this situation is being repeated. Therefore, the target area of this research is the slopes of high land, by using 2D and 3D Lidar data for the analysis of the cultivated area. Experiment was carried out in the same area to compare the data differences. The rate of change in the area of slope is quantitatively increasing presented by the regression model. An alternative methodology that can improve the reliability of the calculated slope area using 2D is through cadastral map.