• 국제지역연구
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• 제12권3호
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• pp.171-194
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• 2008

이 논문은 1980:1-2006:3분기간 자료를 이용하여 한국의 광의통화(M2)와 광의유동성(L)에 대한 개방형 화폐수요함수를 계절성과 외환위기를 고려한 공적분 검정 및 오차수정모형으로 분석하였다. 실증 분석결과 한국의 광의통화(M2)와 광의유동성(L)은 실질소득, 회사채수익률, 인플레이션 불확실성, 실질실효환율, 환율불확실성, LIBOR금리간 공적분 관계가 존재하여 이들 변수들 사이에 안정적인 장기균형관계가 성립하는 것으로 나타났다. 또한 광의통화(M2)변동은 환율불확실성 변화에 가장 크게 의존하며 LIBOR금리 변화와 미세하지만 실질실효환율 및 소득변화에 의해 영향을 받는 것으로 나타났다. 광의유동성(L)의 경우에는 환율불확실성의 변화에 가장 크게 의존하며 광의유동성 수요와 실질소득변화에 의해서도 영향을 받는 것으로 나타났으나, 회사채수익률, 인플레이션불확실성, 실질실효환율, LIBOR금리 등의 변화에 의해서는 영향을 받지 않는 것으로 밝혀졌다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.2309-2318
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• 2010

It is a plan the government increases a railroad section SOC investment, and to activate railroad construction while a railroad wins the spotlight with green transportation. But an error of the demand forecast that is a base of a railroad investment evaluation follows in occurring big, there is it with an operation with an obstacle of a railroad investment. Case of the Incheon International Airport Railroad which went into operation recently, While a present transportation demand showed about 10% than a demand forecasted in a past conference, it was magnified in a social problem. A lot of research was gone on in road project about traffic demand forecast and error, a study to find out the error cause is an insufficient situation although errors of a railroad occurs big. So, this study looked for errors and causes about trip generation model and modes sharing model of railroad demand forecast but it was defined causes so that it can occur similar problems in the future. Especially it investigated causes after comparing rate of development plan for the realization and O/D size in trip generation model and after comparing rate of modes sharing of past and current and conducting a survey for airport users. In conclusion, it suggested method to reduce errors of railroad demand forecasting in the future.

• 대한통합의학회지
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• 제6권4호
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• pp.149-169
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• 2018

Purpose : This study was to develop a strategy for modeling future workforce projections to serve as a basis for analyzing annual supply of and demand for physical therapists across the South Korea into 2030. Methods : In-and-out movement model was used to project the supply of physical therapists. The demand was projected according to the demand-based method which consists of four-stages such as estimation of the utilization rate of the base year, forecasting of health care utilization of the target years, forecasting of the requirements of clinical physical therapists and non-clinical physical therapists based on the projected physical therapists. Results : Based on the current productivity standards, there will be oversupply of 39,007 to 40,875 physical therapists under the demand scenario of average rate in 2030, undersupply of 44,663 to 49,885 under the demand scenario of logistic model, oversupply of 16,378 to 19,100 under the demand scenario of logarithm, and oversupply of 18,185 to 20,839 under the demand scenario of auto-regressive moving average (ARIMA) model in 2030. Conclusion : The result of this projection suggests that the direction and degree of supply of and demand for physical therapists varied depending on physical therapists productivity and utilization growth scenarios. However, the need for introduction of a professional physical therapist system and the need to provide long-term care rehabilitation services are actively being discussed in entering the aging society. If community rehabilitation programs for rehabilitation of disabled people and the elderly are activated, the demand of physical therapists will increase, especially for elderly people. Therefore, healthcare policy should focus on establishing rehabilitation service infrastructure suitable for an aging society, providing high-quality physical therapy services, and effective utilization of physical therapists.

• 전기학회논문지
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• 제59권11호
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• pp.1964-1970
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• 2010

A new intelligent power network (Smart Grid) that grafts some new technologies, such as the extension of the new and reproducible energy, electric motors, and electric storages, onto the regulation of green house gases according to the recent convention on climate changes has been actively promoted. As establishing such an intelligent power network, it is possible to implement a real-time rate system according to the change from the conventional single directional information transmission to the bidirectional information transmission. Such a real-time rate system can provide power during the chip rate hour by avoiding the high rate hour although customers use the same level of power through providing such real-time rate information including power generation costs. In this study, the establishment of an operating system that makes an effective use of the real-time rate system and its operation method are to be proposed.

• 한국항행학회논문지
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• 제21권4호
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• pp.365-370
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• 2017

본 연구는 전력수요 패턴이 다른 평일과 특수일 데이터가 가지는 상관관계를 분석하여, 별도의 데이터 셋을 구축하고, 각 데이터 셋에 적합한 딥 러닝 네트워크를 이용하여, 전력수요예측 오차를 감소하는 방안을 제시하였다. 또한, 기본적인 전력수요 예측요소인 기상요소에 환경요소, 구분요소 등 다양한 예측요소를 추가하여 예측율을 향상하는 방안을 제시하였다. 전체데이터는 시계열 데이터 학습에 적합한 LSTM을 이용하여 전력수요예측을 하였으며, 특수일 데이터는 DNN을 이용하여 전력수요예측을 하였다. 실험결과 기상요소 이외의 예측요소 추가를 통해 예측율이 향상되었다. 전체 데이터 셋의 평균 RMSE는 LSTM이 0.2597이며, DNN이 0.5474로 LSTM이 우수한 예측율을 보였다. 특수일 데이터 셋의 평균 RMSE는 0.2201로 DNN이 LSTM보다 우수한 예측율을 보였다. 또한, 전체 데이터 셋의 LSTM의 MAPE는 2.74 %이며, 특수 일의 MAPE는 3.07 %를 나타냈다.

• 대한산업공학회지
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• 제27권3호
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• pp.233-238
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• 2001

This paper deals with demand forecasting of parts in an automobile model which has been extinct. It is important to estimate how much inventory of each part in the extinct model should be stocked because production lines of some parts may be replaced by new ones although there is still demands for the model. Furthermore, in some countries, there is a strong regulation that the automobile manufacturing company should provide customers with auto parts for several years whenever they are requested. The major characteristic of automobile parts demand forecasting is that there exists a close correlation between the number of running cars and the demand of each part. In this sense, the total demand of each part in a year is determined by two factors, the total number of running cars in that year and the failure rate of the part. The total number of running cars in year k can be estimated sequentially by the amount of shipped cars and proportion of discarded cars in years 1, 2,$\cdots$, i. However, it is very difficult to estimate the failure rate of each part because available inter-failure time data is not complete. The failure rate is, therefore, determined so as to minimize the mean squared error between the estimated demand and the observed demand of a part in years 1, 2,$\cdots$, i. In this paper, data obtained from a Korean automobile manufacturing company are used to illustrate our model.

• 대한건축학회논문집:계획계
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• 제34권8호
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• pp.13-22
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• 2018

The purpose of this study was to consider the energy generation of the building as well as the energy demand of the building in terms of zero energy building design. The reason why the zero energy building viewpoint should be discussed is that direction of the building, heat transfer rate of the building, and the S/V ratio of the building are variables related to energy demand and solar panels installed on the building roof and building envelope are variables related to energy generation. This study proceeded as follows; Firstly, the simulation model of large office and elementary school has the same mutual volume and total floor area, and the each floor area and number of floors are adjusted so that the S/V ratio is different. To the next, the energy demand and energy generation of the simulation model were derived based on the meteorological data of Seoul, Daejeon, Busan. Finally, energy demand, energy generation, and final energy demand were compared with heat transfer rate, S/V ratio, building type, region, and orientation. The results of this study is that consideration of solar power generation in terms of energy generation should be taken into consideration at the same time in consideration of the heat transfer rate, the shape, the region and the direction of the zero energy building design.

• Journal of applied mathematics & informatics
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• 제4권2호
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• pp.457-468
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• 1997

The present paper deals with an economic order quan-tity model for items deteriorating at some constant rate with demand changing at a known and at a random point of time in the fixed pro-duction cycle.

• 에너지공학
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• 제28권4호
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• pp.82-93
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• 2019

본 연구에서는 기존 열수요 예측 시스템이 공휴일과 같은 특정 일자의 열수요 예측율이 저하되는 문제점을 개선하기 위해 새로운 모델을 제안한다. 제안된 모델은 사계절 혼합형 신경망 모델(Four Season Mixed Heat Demand Prediction Neural Network Model)로서 열수요 예측율 상승하였고, 특히 예측일 유형별(평일/주말/공휴일) 열수요 예측율이 크게 증가하였다. 제안된 모델은 다음과 같은 과정을 통해 선정되었다. 특정 계절에 예측일 유형별로 고른 오차를 갖는 모델을 선정하여 전체 예측 모델을 구성한다. 학습 시간의 단축과 과도학습을 방지하기 위해 구조적으로 단순화된 서로 다른 4개의 모델을 각각 학습한 후에 다양한 조합을 통해 최적의 예측 오차를 보여주는 모델을 선정하였다. 모델의 출력은 예측일의 24시간의 시간대별 열수요이며 총합은 일일 총열수요이다. 이 예측값을 통해 효율적인 열공급 계획을 수립 할 수 있으며, 목적에 따라 출력값을 선택하여 활용할 수 있다. 제안된 모델의 일일 열 총수요 예측의 경우, 전체 MAPE(Mean Absolute Percentage Error, 평균 절대 비율 오차)가 개별 모델의 5.3~6.1%에서 5.2%로 향상되었고, 공휴일 열수요예측은 4.9~7.9%에서 2.9%로 크게 개선되었다. 본 연구에서는 한국 지역난방공사에서 제공한 특정 아파트 단지의 34개월 분량의(2015년 1월~ 2017년10월) 시간단위 열수요 데이터를 활용하였다.

• 대한전기학회논문지:전력기술부문A
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• 제54권8호
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• pp.418-428
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• 2005

In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity markets. Conventional forced outage rates of generators are conceptually combined with maintenance outage of generators and, consequently, effective outage rates of generators are newly defined in order to properly address the probabilistic characteristic of generation in electricity markets. Then, original market demands are classified into several distinct demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the original demand. We have found that generators have different effective outage rates values at each classified demand cluster, depending on the market situation. From this, therefore, it can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be more efficiently analyzed in electricity markets perspectives, for this classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.