• 전기학회논문지P
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• 제58권4호
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• pp.505-510
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• 2009

In this paper, building energy analysis and energy cost of power stand up and demand control over the power proposed to reduce power demand. Through analysis of the load power demand special day were able to apply the pattern. In addition, the existing rate of change of load forecasting to reduce the large errors were not previously available data. And daily schedules and special day for considering the exponential smoothing methods were used. Previous year's special day and the previous day due to the uncertainty of the load and the model components were considered. The maximum demand power control simulation using the fuzzy control of power does not exceed the contract. Through simulation, the benefits of the proposed energy-saving techniques were demonstrated.

• Industrial Engineering and Management Systems
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• 제6권2호
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• pp.106-118
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• 2007

This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

• 대한전기학회논문지:전력기술부문A
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• 제51권9호
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• pp.417-424
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• 2002

This paper presents an industrial peak load management system for the peak demand control. Kohonen neural network and wavelet transform based techniques are adopted for industrial peak load forecasting that will be used as input data of the peak demand control. Firstly, one year of historical load data of a steel company were sorted and clustered into several groups using Kohonen neural network and then wavelet transforms are applied with Biorthogonal 1.3 mother wavelet in order to forecast the peak load of one minute ahead. In addition, for the peak demand control, composite fuzzy model is proposed and implemented in this work. The results are compared with those of conventional model, fuzzy model and composite model, respectively. The outcome of the study clearly indicates that the composite fuzzy model approach can be used as an attractive and effective means of the peak demand control.

• 한국항공운항학회지
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• 제16권1호
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• pp.46-57
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• 2008

Since the 90's, Korean Air transport market has been more expanded because of economic growth, the construction of airport infrastructure, and the advent of low cost carrier. Especially, the air traffic demand in Busan metropolitan area has been increasing steadily. Therefore, in this paper, we developed a new forecasting model which could expect the future air traffic demand in Busan area. This model is developed by regression analysis using social-economic variables such as GRDP, income, and the number of people, and dummy variables, for instance, KTX opening, Japan economic depression, SARS and so on. Result from demand forecasting by this new model suggests that the new airport system is needed in order to sustain the increasing air traffic demand in Busan area.

• 전기학회논문지
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• 제63권11호
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• pp.1503-1510
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• 2014

This study organizes scenarios on the power supply plans and electricity load forecasts considering their uncertainties and estimates natural gas quantity for electricity generation, total electricity supply cost and air pollutant emission of each scenario. Also the analysis is performed to check the properness of government's natural gas demand forecast and the possibility of achieving the government's CO2 emission target with the current plan and other scenarios. In result, no scenario satisfies the government's CO2 emission target and the natural gas demand could be doubled to the government's forecast. As under-forecast of natural gas demand has caused the increased natural gas procurement cost, it is required to consider uncertainties of power plant construction plan and electricity demand forecast in forecasting the natural gas demand. In addition, it is found that CO2 emission target could be achieved by enlarging natural gas use and demand-side management without big increase of total costs.

• 한국조경학회지
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• 제21권3호
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• pp.51-64
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• 1993

Meeting the rapidly increasing demand for natural outdoor recreation, Korea Forestry Administration established 26 places of $\ulcorner$Natural Recreation Forest$\lrcorner$ zones. By 2000 year, 100 zones were planned to cover the entire country. But there was no accurate information about demand of $\ulcorner$Natural Recreation Forest$\lrcorner$. Therefore, this study was carried out to forecast the quantitive demand of $\ulcorner$Natural Recreation Forest$\lrcorner$. To forecast the 'demand of 2001 year, forecasting unit was determined to $\ulcorner$Visitor. Day$\lrcorner$, and three quantifing methods were applied. The results of demand by each forecating method were as follows: 1) Questionnaire survey method for willingness to participate was 16,651,000(visitor. day). 2) application of similiar situation threshold method was 14,540,000(visitor. day). 3) Demand partition method by secondary data was 10,775,000(visitor, day). Comprised of these results. The scope estimate of $\ulcorner$Natural Recreation Forest$\lrcorner$ demand was proposed as 8,110,000(Minimum) - 27,088,000(Miximum). The point estimate of demand which were proposed as strategic guidelines was 16,651,000(visitor. day). These results implied that recently announced 111 predetermined $\ulcorner$Natural Recreation Forest$\lrcorner$ zones supposed to be overcrowded meeting the forcasted demand level of 2001 year.

• 응용통계연구
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• 제22권5호
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• pp.1019-1032
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• 2009

도시가스 수요량은 강한 계절성을 보이는 자료이다. 따라서 도시가스 수요량을 예측하기 위한 모형 구축에서 가장 중요한 요인은 계절성이다. 또한, 실제 도시가스 수요량에는 추가적 인 여러 요인들에 의하여 영향을 받을 수 있는데, 온도, 요일효과, 명절효과, 유효일 수, 수용가수 등이 영향 요인들이다. 본 연구에서는 이와 같은 요인들이 도시가스 수요량에 미치는 영향력의 정도를 파악하고 효율적으로 향후 도시가스 수요량 예측을 위한 시계열 모형을 구축하였다. 적용된 모형은 오차항이 자기상관을 따르는 시계열 회귀모형을 이용하였으며 실제 자료를 이용한 예측결과 매우 우수한 예측력을 보였다.

• 한국차세대컴퓨팅학회논문지
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• 제13권4호
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• pp.7-18
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• 2017

현대사회에서 가장 중요한 에너지원 중 하나인 전력 에너지는 적절한 수요 공급 조절이 매우 중요하다. 하지만 수요 예측을 위해 필요한 전력데이터는 전력 사용자의 행위에 대한 정보가 포함 될 수 있어, 이를 분석할 경우 프라이버시 침해 문제로 이어질 수 있다. 이에 본 논문에서는 사용자의 전력 사용 정보에 회귀 분석을 적용하여 사용자의 향후 전력 사용량을 예측하되, Intel SGX가 제공하는 안전한 실행 환경 상에서 이를 수행함으로써 사용자의 전력 사용 정보를 안전하게 보호하는 방법을 제안한다. 다양한 차수의 회귀 관계식에 대한 실험을 수행하여 오차를 최소로 하는 회귀 관계식을 선정하였으며, 제안하는 방법을 이용하면 프라이버시 보호 기능을 제공하는 기존의 전력 수요 예측 방법보다 낮은 평균오차율을 보임을 확인하였다.

• 기술혁신학회지
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• 제14권spc호
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• pp.1232-1255
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• 2011

본 연구에서는 신제품 확산 모델 활용에 있어서 보다 적은 노력이 필요하지만 객관적이고 신속한 활용을 가능하게 만들어줄 모형을 제안한다. 기대주기 모델과 소비자 수용 모델이라는 이론적 배경을 바탕으로, 서지분석학과 초기 시장의 규모만으로 최대 잠재 시장을 추정해냄으로써 대표적인 확산 모형인 배스 모형(Bass model)에 필요한 주요 모수를 제공하는 방법을 제시했다. 모형의 예측력을 하이브리드자동차 사례를 통해 분석한 결과, 모형의 예측결과는 여러 가지 객관적인 정보를 통해 추정한 잠재 시장과 유사한 규모를 성공적으로 예측해 내어 모형의 활용 가능성을 확인할 수 있었다. 제안된 모형이 제공한 최대 잠재 시장은 다른 성장곡선모형에도 바로 적용 가능하다는 점을 볼 때 제안된 모형은 서지분석학을 통한 기술 확산 예측과 유망기술 탐색에 새로운 방향을 제시했다고 할 것이다.

• 한국전자통신학회논문지
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• 제9권1호
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• pp.131-136
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• 2014

본 논문에서는 패션 상품 수요 예측을 위하여 ARIMA 모형과 웨이블렛 신경회로망 모형을 결합한 상품 수요 예측 알고리즘을 개발하였다. 제시된 방법을 검증하기 위하여 2008년에서 2012년까지의 H사의 패션 상품 데이터를 바탕으로 다양한 알고리즘을 축하고 제안한 방법의 정확도를 분석하였다. 실험 결과 ARIMA 모형은 MAPE가 5.179%, 웨이블렛 신경회로망은 4.553%, 제안한 ARIMA + 웨이블렛 신경회로망 모형은 4.448%로 나타나 성능이 우수한 것으로 나타났다. 따라서 제안된 방법을 사용할 경우 패션 상품 수요 예측을 위해 유용하게 활용할 수 있음을 보였다.