• Journal of the Korean Society of Safety
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• v.4 no.1
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• pp.103-120
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• 1989

최근 도시교통계획분야에 있어서 교통수요의 예측모델 또는 교통정책의 평가 모델로서 비집계(非集計) 모델에 관한 연구가 진행되고 있다. 이 비집계모델은 개개의 의사결정단위에 있어서 선택행동을 영역마다 집계하는 것이 아니고 의사결정레벨의 데이터률 그대로 모델로 구성할 경우 이 데이터를 이용함으로써 의사결정단위의 선택행동을 모델화 할 수 있다는 특징을 갖고 있다. 한편 비집계모델의 사용목적은 여러가지로 생각되나 이것을 교통수요의 목적이나 교통정잭의 평가를 위한 모델로 이용할 때는 파라미터의 추정값이나 선택비율의 추정값에 대한 안정성이 매우 중요한 문제가 되고 있다.

• Land and Housing Review
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• v.5 no.4
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• pp.247-257
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• 2014

This study proposes a new housing need and demand assessment model centering on small-scale housing development projects and happy house development projects that reflected the recent changes in rental and small sized apartment centered public housing policies and development paradigms. The housing need and demand assessment model of public housing development projects consists of quantitative evaluation factors such as potential need indicator and demand pressure indicator and qualitative evaluation factors such as local condition indicator. The potential need indicators of small sized housing development projects are calculated by subtracting the stock of already-supplied constructed rental and purchased rental housings from the potential quantity of need drawn from the small regions such as -eup, -myeon, and -dong. In the potential need indicators of happy house development projects, the potential need is calculated from those who are expected to receive a happy house in the unit of -si, -gun, and -gu. In small-sized housing development projects, demand pressure indictors are the number and the proportion of those who opened a subscription deposit, the number of those who received basic livelihood security and the number of those who were patriots and veterans. The demand pressure indicators of the happy house development projects are stock ratio of small-sized houses, rate of rise in housing rent price, level of housing rent price, and rate of monthly rent house.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.281-289
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• 2008

In this study, a discrete-event simulation model is developed to estimate load factors and the corresponding revenues under different pricing and dispatching policies. The model has been employed to forecast the inbound and the outbound air cargo demands of the major Northeastern Chinese cities, and the simulation results were compared to the actual demands obtained from real-life airline operations. The statistical analysis confirms that the simulation model is able to provide accurate estimates for air cargo demands, and thus, the model may be employed to be a useful tool for air cargo demand management.

• International Commerce and Information Review
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• v.16 no.3
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• pp.73-96
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• 2014

The purpose of this research is to evaluate a short-term export demand forecasting model reflecting individual passenger vehicle brands and market characteristics by using Vector Autoregressive (VAR) models that are based on multivariate time-series model. The short-term export demand forecasting model was created by discerning theoretical potential factors that affect the short-term export demand of individual passenger vehicle brands. Quarterly short-term export demand forecasting model for two Korean small vehicle brands (Accent and Avante) were created by using VAR model. Predictive value at t+1 quarter calculated with the forecasting models for each passenger vehicle brand and the actual amount of sales were compared and evaluated by altering subject period by one quarter. As a result, RMSE % of Accent and Avante was 4.3% and 20.0% respectively. They amount to 3.9 days for Accent and 18.4 days for Avante when calculated per daily sales amount. This shows that the short-term export demand forecasting model of this research is highly usable in terms of prediction and consistency.

• Water for future
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• v.54 no.10
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• pp.32-38
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• 2021

• Proceedings of the Technology Innovation Conference
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• 2003.02a
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• pp.173-190
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• 2003

Demand forecasting is essential in establishing national and corporate strategy as well as the management of their resource. We forecast demand for multi-generation product using discrete choice model combining diffusion model The discrete choice model generally captures consumers'valuation of the product's qualify in the framework of a cross-sectional analysis. We incorporate diffusion effects into a discrete choice model in order to capture the dynamics of demand for multi-generation products. As an empirical application, we forecast demand for worldwide DRAM (dynamic random access memory) and each of its generations from 1999 to 2005. In so doing, we use the method of 'Technological Forecasting'for DRAM Density and Price of the generations based on the Moore's law and learning by doing, respectively. Since we perform our analysis at the market level, we adopt the inversion routine in using the discrete choice model and find that our model performs well in explaining the current market situation, and also in forecasting new product diffusion in multi-generation product markets.

• 수도
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• v.23 no.6 s.81
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• pp.36-46
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• 1996

급수 수요량의 단기예측은 상수도 시스템의 유지관리 계획 수립의 중요한 구성 요소이며, 대상지역의 특성을 민감하게 반영하고 있으므로, 급수수요의 지역 특성과 관련된 수요 구조의 파악이 무엇보다 중요한 과제라 할 수 있다. 따라서 본 논문에서는 상수도 시스템의 합리적 배수 제어 획을 실시하기 위한 기초적 정보인 급수량 변동 구조에 대해 통계적인 분석을 실시하였다. 특히 일단위의 급수량에 초점을 두어 급수량의 시계열 특성과 급수량 영향 요인 분석을 통하여 대상 지역의 정상 시계열장과 급수량에 영향을 미치는 요인을 분석하였다. 또한 급수량의 계절별 단기 수요 예측 모델을 제안하기 위하여 통계적 예측 수법으로 평가 받고 있는 MARIMA (Multiple Auto Regressive Integrated Moving Average) 모델을 급수량 단기 수요 예측에 적용하여 계절별 급수 수요량을 예측하였다.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.406-415
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• 2018

Educational satisfaction is an important indicator of the educational field but the existing customer satisfaction index mainly focused on partial area because measurements could not reflect the alteration of university environment. The purpose of this research is to develop a new UCSI for university to improve the quality of university education. This research demonstrates validity and reliability of UCSI. This research uses the second-order confirmatory factor analysis. The results indicate that the reliability and validity of UCSI is verified. Education condition, education course, university development and student support are clarified to be appropriate components of the satisfaction survey. This research develops UCSI and applies it in a university. University managers can be used to measure the satisfaction level of university education and to improve the quality of university education.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.617-618
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• 2020

우리나라의 지리적인 여건상 대륙과 연결되지 않기 때문에 해상운송에 절대적으로 의존하고 있다. 해상운송에 있어 항만시설의 확보가 필요하며 대외무역의존도가 높은 우리나라의 경우 더욱 중요한 역할을 한다. 항만시설은 장기적인 항만수요예측을 통해 대규모 인프라투자를 결정하며 단기적인 예측은 항만운영의 효율성을 개선하고 항만의 경쟁력을 제고하는데 기여하므로 예측의 정확성을 높이기 위해 많은 노력이 필요하다. 본 논문에서는 딥러닝 모델 중에 하나인 LSTM(Long Short Term Memory)을 적용하여 우리나라 주요항만의 컨테이너 물동량 단기예측을 수행하여 선행연구들에서 주류를 이뤘던 ARIMA류의 시계열모델과 비교하여 예측성능을 평가할 것이다. 본 논문은 학문적으로 항만수요예측에 관한 새로운 예측모델을 제시하였다는 측면에서 의미가 있으며 실무적으로 항만수요예측에 대한 정확성을 개선하여 항만투자의사결정에 과학적인 근거로서 활용이 가능할 것으로 기대된다.

• Proceedings of the KAIS Fall Conference
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• 2010.05b
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• pp.923-927
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• 2010

본 연구는 가격 및 수요 불확실성하의 강건한 (robust) 생산 및 수송 전략을 수립함으로써 수요 및 가격 불확실성이 존재하는 TFT-LCD 제조업 공급사슬망의 의사결정 문제를 해결하고자 한다. 품질로 구분되는 제품들의 생산, 재고 및 물류에 관한 의사결정을 조정하기 위해, 본 연구에서는 생산용량 제약, 해상/항공 수송 리드타임 및 용량 제약 등의 현실적인 제약조건들 이외에 시나리오 모델을 이용하여 수요 및 가격 불확실성을 함께 반영하는 확률적 혼합정수선형계획법모형들을 개발한다. 또한 이들 모형들의 효율적 솔루션을 위해 제안한 휴리스틱 알고리즘의 성능을 평가하도록 한다.