• 한국철도학회:학술대회논문집
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• 한국철도학회 2001년도 추계학술대회 논문집
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• pp.97.1-103
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• 2001

Railway passenger demand forecasts may be used directly, or as inputs to other optimization model which is use the demand forecasts to produce estimates of other activities. The optimization models require demand forecasts at the most detailed level. In this environment exponential smoothing forecasting methods such as Holt-Winters are appropriate because it is simple and inexpensive in terms of computation. There are several initialization methods for Holt-Winters Model. The purpose of this paper is to compare the initialization methods for Holt-Winters model.

• 경영과학
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• 제26권1호
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• pp.77-91
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• 2009

It is the most important sucess factor for the electricity generation industry to minimize operations cost of surplus electricity generation through accurate demand forecasts. Temperature forecast is a significant input variable, because power demand is mainly linked to the air temperature. This study estimates the information value of the temperature forecast by analyzing the relationship between electricity load and daily air temperature in Korea. Firstly, several characteristics was analyzed by using a population-weighted temperature index, which was transformed from the daily data of the maximum, minimum and mean temperature for the year of 2005 to 2007. A neural network-based load forecaster was derived on the basis of the temperature index. The neural network then was used to evaluate the performance of load forecasts for various types of temperature forecasts (i.e., persistence forecast and perfect forecast) as well as the actual forecast provided by KMA(Korea Meteorological Administration). Finally, the result of the sensitivity analysis indicates that a $0.1^{\circ}C$ improvement in forecast accuracy is worth about $11 million per year.

• 한국환경과학회지
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• 제22권8호
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• pp.965-977
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

• 플랜트 저널
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• 제15권1호
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• pp.31-37
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• 2019

본 연구에서는 지역난방시스템 열수요 예측의 정확도 향상을 위하여 판교지역을 대상으로 지역난방 수요예측 주요인자 중 열수요 실적을 기존의 열원시설 열공급정보 대신 변경된 사용자시설 열판매정보로 적용하여 혹한기를 포함한 5개월 동안의 수요를 예측하고 실적값을 기준으로 기존 방식과 정확도를 비교하였다. 열수요가 피크를 이루는 혹한기 1주일(2018.01.08.~01.14) 동안 실적값을 기준으로 기존 및 변경방식 예측값의 시간대별 차이를 비교한 결과 상대오차가 7%에서 3%로 감소되었으며, 2017년 10월부터 2018년 2월까지 5개월에 걸친 일일 누적 열수요에 있어서도 실적값 대비 기존 및 변경 방식 예측값의 상대오차는 각각 9%와 4%로 변경방식의 상대오차가 감소하였다. 또한, 열수요 특성이 차별화되는 주말의 경우에도 예측값의 상대오차는 기존 방식 10%에서 변경 방식 5%로 일관성 있게 감소함을 확인할 수 있었다.

• Journal of information and communication convergence engineering
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• 제9권4호
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• pp.369-374
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• 2011

Generally the neural network and the Fuzzy compensative algorithms are applied to forecast the time series for power demand with the characteristics of a nonlinear dynamic system, but, relatively, they have a few prediction errors. They also make long term forecasts difficult because of sensitivity to the initial conditions. In this paper, we evaluate the chaotic characteristic of electrical power demand with qualitative and quantitative analysis methods and perform a forecast simulation of electrical power demand in regular sequence, attractor reconstruction and a time series forecast for multi dimension using Lyapunov Exponent (L.E.) quantitatively. We compare simulated results with previous methods and verify that the present method is more practical and effective than the previous methods. We also obtain the hourly predictability of time series for power demand using the L.E. and evaluate its accuracy.

• 한국철도학회논문집
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• 제7권1호
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• pp.9-13
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• 2004

Railway passenger demand forecasts may be used directly, or as inputs to other optimization models use them to produce estimates of other activities. The optimization models require demand forecasts at the most detailed level. In this environment exponential smoothing forecasting methods such as Holt-Winters are appropriate because it is simple and inexpensive in terms of computation. There are several initialization methods for Holt-Winters Model. The purpose of this paper is to compare the initialization methods for Holt-Winters model.

• 에너지공학
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• 제18권2호
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• pp.114-124
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• 2009

지식경제부(MKE)는 매2년마다 전력수급기본계획을 수립한다. 본 논문에서는 전력수급기본계획 수립시 전력수요를 과대 또는 과소로 예측한 것이 차기 전력수급기본계획 수립시 전원혼합(Energy Mix)에 미치는 영향을 정량적으로 평가하였다. 전력수요 자료는 2005년도에 예측한 제3차 전력수급기본계획의 전망치를 이용하였고 전원혼합을 도출하기 위하여 전력거래소(KPX)에서 활용하고 있는 WASP 전산모형을 단순화한 시뮬레이션 모형을 구축하였다. 2005년도 전력수요를 적정, 5% 과대 그리고 5% 과소 예측한 경우에 대하여 각각 단순화한 시뮬레이션 모형을 이용하여 2005년도 전력수급기본계획의 전원혼합을 도출하였다. 이 3가지 전원혼합을 초기조건으로 하여 2005년도의 적정 전력수요가 2007년 이후에 적용된다고 보고 2007년도에 차기 전력수급기본계획의 전원혼합을 도출하였다. 전력수요가 적정일 경우, 2005년도와 2007년도 전력수급 기본계획의 전력수요는 동일하므로 전원혼합에 변화가 없다. 전력수요를 5% 과대 또는 5% 과소 예측한 경우, 계획된 발전소 건설을 차기 전력수급기본계획 수립시 줄이거나 늘려야 하는데 건설기간이 짧은 LNG 발전소가 그 영향을 받는 것으로 나타났다.

• 한국융합학회논문지
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• 제10권8호
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• pp.165-170
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• 2019

2018년 국토교통부의 통계에 따르면, 연평균 항공교통이용자만 국내선 5.07%, 국제선 8.84%가 증가하였다. 한류의 열풍으로 인해 지속적인 외국인 관광객의 수요가 증가하고 있다. 동시에 개인의 삶의 질을 중요시하는 새로운 생활 문화가 자리잡아가고 있으며 이와 더불어 저가 항공사의 출현으로 인해 내국인의 해외 관광 또한 증가하고 있다. 따라서 효율적이고 정확한 항공 수요예측을 진행하여 체계적인 공항 인프라를 조성하는 것이 중요하다. 본 연구에서는 빅 데이터(big data)를 기반으로 하여 도심권 공항의 국내선 및 국제선 장기 수요예측을 진행하였다. 국내선의 경우 2028년 이후 인구 감소에 따라 공항이용객이 다소 감소할 것이며, 국제선은 GDP증가에 따라 지속적으로 증가할 전망이다. 따라서 미래의 항공수요에 대처하기 위해서는 국내 공항의 여객터미널 개선 및 확충이 절실하다.

• 산업경영시스템학회지
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• 제41권1호
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• pp.50-58
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• 2018

Intermittent demand is a demand with a pattern in which zero demands occur frequently and non-zero demands occur sporadically. This type of demand mainly appears in spare parts with very low demand. Croston's method, which is an initiative intermittent demand forecasting method, estimates the average demand by separately estimating the size of non-zero demands and the interval between non-zero demands. Such smoothing type of forecasting methods can be suitable for mid-term or long-term demand forecasting because those provides the same demand forecasts during the forecasting horizon. However, the smoothing type of forecasting methods aims at short-term forecasting, so the estimated average forecast is a factor to decrease accuracy. In this paper, we propose a forecasting method to improve short-term accuracy by improving Croston's method for intermittent demand forecasting. The proposed forecasting method estimates both the non-zero demand size and the zero demands' interval separately, as in Croston's method, but the forecast at a future period adjusted by binomial weight according to occurrence probability. This serves to improve the accuracy of short-term forecasts. In this paper, we first prove the unbiasedness of the proposed method as an important attribute in forecasting. The performance of the proposed method is compared with those of five existing forecasting methods via eight evaluation criteria. The simulation results show that the proposed forecasting method is superior to other methods in terms of all evaluation criteria in short-term forecasting regardless of average size and dispersion parameter of demands. However, the larger the average demand size and dispersion are, that is, the closer to continuous demand, the less the performance gap with other forecasting methods.

• 한국태양에너지학회 논문집
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• 제39권5호
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• pp.29-40
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• 2019

In response to the rapid climate change, in order to save energy in the field of buildings, the country is planning not only zero energy buildings but also zero energy cities. In the Urban Development Project, the Energy Use Plan Report is prepared and submitted by predicting the amount of energy demand at the planning stage. However, due to the activation of zero-energy buildings and the increase in the supply of new and renewable energy facilities, the energy consumption behavior of buildings in the city is changing from the previous ones. In this study, to estimate urban energy demand of Zero Energy City, building energy demand forecasts based on "Passive plans for use of energy based primary energy consumption", "Actual building energy usage data from Korea Appraisal Board" and "data from Certification of Building Energy Efficiency Rating" as well as demand forecast according to existing "Consultation about Energy Use Plan Code" were calculated and then applied to Multifunctional Administrative City 5-1 zone to compare urban total energy demand forecasts.