• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.703-720
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• 2019

The influence of temperature on electricity demand is increasing due to extreme weather and climate change, and the climate impacts involves nonlinearity, asymmetry and complexity. Considering changes in government energy policy and the development of the fourth industrial revolution, it is important to assess the climate effect more accurately for stable management of electricity supply and demand. This study aims to analyze the effect of temperature change on electricity demand using the partial linear model. The main results obtained using the time-unit high frequency data for meteorological variables and electricity consumption are as follows. Estimation results show that the relationship between temperature change and electricity demand involves complexity, nonlinearity and asymmetry, which reflects the nonlinear effect of extreme weather. The prediction accuracy of in-sample and out-of-sample electricity forecasting using the partial linear model evidences better predictive accuracy than the conventional model based on the heating and cooling degree days. Diebold-Mariano test confirms significance of the predictive accuracy of the partial linear model.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.111-122
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• 2007

This paper investigates the rail service patterns by train class. The emphasis in intercity rail planning is to more efficiently use of existing station facilities. Rail transit operations are affected by the system layout and ridership patterns and by work rules. Operations are also influenced by past practices and the institutional setting. Main factors to decide train service patterns are the location, socioeconomic characteristics, land use and travel demand of the station. In this context, the travel demand of intercity rail station is of crucial significance. Tests on a KTX case shows that train service frequency can be efficiently decreased in weekday to transport the same passenger demand. The work has shown many subjects that need further research including various factors influencing on train frequency. This study serves the railroad authorities in planning and determining business strategy in the increasingly competitive environment of regional rail transport.

• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.7-15
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• 2008

Due to the limitations in the statistical data, the existing studies adopted rough methodologies with strong assumptions in the estimation of international passenger travel demand forecast in the ASEAN region. This study aims to develop international passenger travel demand models using scientific methodologies. This study proposes a direct demand model using the immigration and emigration data between countries in the region. This is because of the difficulty of estimating trip generation and trip distribution separately due to the data limitation in the region. As there does not exist the mode choice model for the region, this study estimates a mode choice model using the Stated Preference technique. The mode choice model is separated into three categories of models according to the range of distance between the origin and destination of travel; this is to reflect the different behavior in mode choice according to the travel distance. The result of model estimations suggests that the estimated models produce resonable results statistically. It is expected that the proposed models are useful for the future travel demand estimation in the ASEAN region.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.2
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• pp.67-78
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• 2019

Accurate electric load forecasting is very important in the efficient operation of the smart grid. Recently, due to the development of IT technology, many works for constructing accurate forecasting models have been developed based on big data processing using artificial intelligence techniques. These forecasting models usually utilize external factors such as temperature, humidity and historical electric load as independent variables. However, due to diverse internal and external factors, historical electrical load contains many missing data, which makes it very difficult to construct an accurate forecasting model. To solve this problem, in this paper, we propose a random forest-based missing data recovery scheme and construct an electric load forecasting model based on multilayer perceptron using the estimated values of missing data and external factors. We demonstrate the performance of our proposed scheme via various experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.234-241
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• 2021

By recognizing the importance of demand forecasting, the military is conducting many studies to improve the prediction accuracy for repair parts. Demand forecasting for repair parts is becoming a very important factor in budgeting and equipment availability. On the other hand, the demand for intermittent repair parts that have not constant sizes and intervals with the time series model currently used in the military is difficult to predict. This paper proposes a method to improve the prediction accuracy for intermittent repair parts of the Patriot. The authors collected intermittent repair parts data by classifying the demand types of 701 repair parts from 2013 to 2019. The temperature and operating time identified as external factors that can affect the failure were selected as input variables. The prediction accuracy was measured using both time series models and data mining models. As a result, the prediction accuracy of the data mining models was higher than that of the time series models, and the multilayer perceptron model showed the best performance.

• The monthly packaging world
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• s.75
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• pp.92-97
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• 1999

97년 IMF와 함께 침체된 경기가 좀처럼 살아나지 않고 있는데 이러한 경향은 OPP,CPP,PET필름 업계에서도 예외는 아니다. 이러한 이유로 지난 해 한정된 시장 나눠먹기에 불과했던 필름 업계는 올해는 경기가 호전 될것으로 긍정적으로 기대하고 있으나 상반기를 지낸 현재 이를 기대할 수 있는 큰 변수는 없는 것으로 잠정 평가되고 있다.

• 주택과사람들
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• s.224
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• pp.34-38
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• 2008

새해가 밝았지만 건설 업계의 불안감은 더욱 가중되고 있다. 경제불황으로 그나마 살아 있던 주택 수요마저 얼어붙었다. 결국 정부는 경기 회복을 위해 각종 부동산 규제를 푸는 등 초강수를 두고 있다. 지금은 미국 경제의 회복 같은 외생적 변수들의 긍정적 시그널이 필요할 때다. 주택시상 연착륙을 위한 방안을 모색해 보자.

• The Optical Journal
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• v.13 no.2 s.72
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• pp.49-55
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• 2001

레이저 용접은 매우 작은 점으로 집속된 높은 밀도의 에너지로 재료를 용융시키는 용접방법으로, 좁고 깊은 용접부를 얻을 수 있으며 출력만 충분하면 단 1회의 용접으로도 상당히 깊은 용접부를 쉽게 얻는다는 장점이 있다. 레이저 용접의 원리와 특징, 레이저 용접 공정 변수, 레이저 용접공정의 관리, 산업현장에서의 레이저 용접기술 적용 현황을 알아본다.

• 주택과사람들
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• s.202
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• pp.92-94
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• 2007

9월부터 실시될 민간 택지의 분양가 상한제 확대 및 청약 제도 개편으로 올해 주택 분양 시장은 변수가 많아졌다. 주택 공급자들은 분양가 상한제로 인해 공급 시점을 두고 옥신각신하고, 주택 수요자들은 청약 제도 개편으로 인한 청약 시점을 두고 저울질한다. 청약 가점제로 인해 달라지는 내용과 청약 유망 지역을 실수요자 입장에서 접근해보자.

• Fire Science and Engineering
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• v.21 no.3
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• pp.24-32
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• 2007

The environment of fire service is more uncertain as cities become complicated and new combustibles are used. If fire service's budget is not allocated sufficiently for fire facilities and equipment, fire service's quality and firefighter's safety are affected seriously. Therefore project budget must be increased to prevent fire and disaster effectively. This study investigate the change of fire service demands, the change and priority of fire service budget and project budget. And this study examined the relationship between fire service demand and project budget using correlation and regression analysis. Analysis showed that a number of rescue and emergency medical service were significant variable for project budget.