• Environmental Engineering Research
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• 제15권3호
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• pp.135-140
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• 2010

With the various urban characteristics of each city, the existing water demand prediction, which uses average liter per capita day, cannot be used to achieve an accurate prediction as it fails to consider several variables. Thus, this study considered social and industrial factors of 164 local cities, in addition to population and other directly influential factors, and used main substance and cluster analyses to develop a more efficient water demand prediction model that considers unique localities of each city. After clustering, a multiple regression model was developed that proved that the $R^2$ value of the inclusive multiple regression model was 0.59; whereas, those of Clusters A and B were 0.62 and 0.74, respectively. Thus, the multiple regression model was considered more reasonable and valid than the inclusive multiple regression model. In summary, the water demand prediction model using principal component and cluster analyses as the standards to classify localities has a better modification coefficient than that of the inclusive multiple regression model, which does not consider localities.

• 한국경영과학회지
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• 제42권1호
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• pp.29-41
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• 2017

Korea is expected to become a super-aged society by 2050. Given an aging population and the increasing pressure for the early retirement, a sufficient social safety net for elderly population becomes important. The Korean government introduced public reverse mortgage program in 2007, which is a product for aging seniors and the elderly, The number of reverse mortgage subscribers has also steadily grown. The demand continues to grow, but the reverse mortgage over a long period of time is a highly uncertain and risky product in the position of guarantee or lending institution. Thus, suitable demand prediction of the reverse mortgage subscribers is necessary for stable and sustainable operation. This study uses a Bass diffusion model to forecast the long-term demand for reverse mortgage and provides insight into reverse mortgage by forecasting demand for stability and substantiality of the loan product. We represent the projections of new subscribers on the basis of the data obtained from Korea Housing Finance Corporation. Results show that potential market size of Korean reverse mortgage reaches approximately 760,000-1,160,000 households by 2020. We validate the results by comparing the estimate of the cumulative number of subscribers with that found in literature.

• 한국시뮬레이션학회논문지
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• 제15권3호
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• pp.39-47
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• 2006

대부분의 공급망 계획에서 사용되는 각 계획 기간 내의 예측수요는 확정적인 것으로 간주한다. 그러나 현실에서 주어진 계획 기간 내의 수요 예측값은 확률적으로 분포를 따르는 것이 일반적이다. 본 연구는 기존의 안전재고를 통한 서비스 수준을 관리하는 방법을 대신하여 고객 수요의 분포내의 특정한 값을 수요 예측값으로 사용하는 수요선택 방법에 대해 다룬다. 수요 분위수와 계층 재고의 개념을 활용하여 서비스 수준 제약이 존재하는 시리얼 재고시스템을 대상으로 비교적 간단하지만 효과적인 수요선택을 위한 휴리스틱 알고리듬을 제안한다. 시뮬레이션을 활용한 비교 실험을 통해 제안된 알고리듬이 최적해와 유사한 매우 정확한 결과를 보임을 입증하였다.

• 토지주택연구
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• 제9권4호
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• pp.10-18
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• 2018

As the volatility increasement of the number of tourist, there was been controversy over supply-demand imbalance in hotel market. The purpose of this study is to analysis on determinants of hotel occupancy rate in Jeju Island. The quantitative method is based on cointegrating regression, using an empirical dataset with hotel from 2000 to 2017. The primary results of research is briefly summarized as follows; First, there are high relationship between total hotel occupancy rate and hotel occupancy of foreign tourist. The volatility of hotel occupancy is caused by foreigner user than local tourists though local tourist high propotion of hotel occupancy in Jeju Island. Second, hotel occupancy of local tourist has not relationship with demand and supply variables. Because some hotel users are not local tourists but local resident, and effects to other variables of hotel consumer trend, accommodation such as Guest house, Airbnb. Third, there are high relationship between foreign hotel occupancy rate and demand-supply variables. These research imply that total management of supply-demand is very important to seek stability of hotel occupancy rate in Jeju Island. Also it can provide a useful solution regarding mismatch problem between supply-demand as well as development the systematic forecasting model for hotel market participants.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권3호
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• pp.528-550
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• 2024

Warehousing demand prediction is an essential part of the supply chain, providing a fundamental basis for product manufacturing, replenishment, warehouse planning, etc. Existing forecasting methods cannot produce accurate forecasts since warehouse demand is affected by external factors such as holidays and seasons. Some aspects, such as consumer psychology and producer reputation, are challenging to quantify. The data can fluctuate widely or do not show obvious trend cycles. We introduce a new model for warehouse demand prediction called MAGRU, which stands for Multi-layer Attention with GRU. In the model, firstly, we perform the embedding operation on the input sequence to quantify the external influences; after that, we implement an encoder using GRU and the attention mechanism. The hidden state of GRU captures essential time series. In the decoder, we use attention again to select the key hidden states among all-time slices as the data to be fed into the GRU network. Experimental results show that this model has higher accuracy than RNN, LSTM, GRU, Prophet, XGboost, and DARNN. Using mean absolute error (MAE) and symmetric mean absolute percentage error(SMAPE) to evaluate the experimental results, MAGRU's MAE, RMSE, and SMAPE decreased by 7.65%, 10.03%, and 8.87% over GRU-LSTM, the current best model for solving this type of problem.

• 아태비즈니스연구
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• 제14권4호
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• pp.343-356
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• 2023

Purpose - This study attempted to predict short-term transportation demand using trains and getting off at Gangchon Station. Through this, we present numerical data necessary for future tourist inflow policies in the Gangchon area of Chuncheon and present related implications. Design/methodology/approach - This study collected and analyzed transportation demand data from Gangchon Station using the Gyeongchun Line and ITX-Cheongchun Train from January 2014 to August 2023. Winters exponential smoothing model and ARIMA model were used to reflect the trend and seasonality of the raw data. Findings - First, transportation demand using trains to get off at Gangchon Station in Chuncheon City is expected to show a continuous increase from 2020 until the forecast period is 2024. Second, the number of passengers getting off at Gangchon Station was found to be highest in May and October. Research implications or Originality - As transportation networks are improving nationwide and people's leisure culture is changing, the number of tourists visiting the Gangchon area in Chuncheon City is continuously decreasing. Therefore, in this study, a time series model was used to predict short-term transportation demand alighting at Gangchon Station. In order to calculate more accurate forecasts, we compared models to find an appropriate model and presented forecasts.

• 디지털융복합연구
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• 제11권2호
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• pp.175-182
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• 2013

본 연구에서는 주택 수요와 공급의 상호영향관계 메커니즘을 이용하여 가격 시뮬레이션 모형을 개발하였다. 가격 시뮬레이션 모형의 핵심 알고리즘은 피드백 제어 이론을 이용한 시스템 다이나믹스 기반의 스톡 플로우 변수이며, 이러한 원리를 이용하여 서울지역 아파트 가격변화 행태를 모델링하였다. 가격 행태를 결정하는 피드백 메커니즘은 중장기 경기변동 시나리오 하에 대출 이자율을 정책변수로 아파트 매매 수요자와 공급자 규모를 스톡 변수로 설정하고, 이들 간의 상호 영향관계를 검증하였다. 본 논문을 통하여 향후 아파트 가격 추이는 아파트 매매 수요자와 공급자 규모의 행태 변화와 수요자와 공급자가 갖는 가격에 대한 반응 매개변수간의 영향관계로 구성된다. 또한 향후 경기 전망 및 대출이자율 등 거시경제의 상황에 따라 아파트 매매가격은 변화함을 알 수 있었다. 제시된 아파트 매매 가격 시뮬레이션 계량모델은 양도세 및 취득세 감면 등 비 금융 관련 부동산정책변수와 대출이자 조정 등 금융 관련 정책변수의 보다 정확하고 충분한 데이터를 적용하면 실무 적용과 정부 주택정책입안에 활용 할 수 있을 것으로 판단된다.

• 대한교통학회지
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• 제24권3호
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• pp.197-205
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• 2006

본 연구에서는 복합대중교통체계 하에서 환승을 명확하게 반영하면서 신교통수단의 수요를 분석할 수 있는 분석기법을 제안하였다. 제안된 분석방법은 통행특성별로 그룹을 나누어 각 그룹별로 별도의 적합한 교통수요모형을 적용함으로써 좀 더 현실적인 교통수요분석이 가능하도록 하였다. 구체적으로 신교통수단만 이용하는 통행수요(신교통수단 노선구간 내 통행), 신교통수단을 이용하여 출발하거나 도착하는 통행수요(신교통수단 노선구간 내-외부 통행), 신교통수단의 노선을 통과하는 통행수요(신교통수단 노선구간 통과 통행)로 구분하여 통행의 특성별로 적합한 교통수요분석방법을 별도로 적용할 것을 제안하였다. 또한 본 연구에서는 신교통수단 정책과 같이 승용차에서 대중교통으로의 수단 전환이 가능한 정책 분석에서 사업 시행시와 사업 미시행시 간의 수단별 O/D 값에 차이가 있을 때에도 동일한 지표에 의해 일관된 정책평가 결과를 제시할 수 있는 통행시간 편익산출 방법도 제안하였다.

• 한국문헌정보학회지
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• 제50권3호
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• pp.155-169
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• 2016

본 연구는 19대 전반기 국회의원의 속성에 따른 입법정보 이용행태에 대한 분석을 통해 20대 전반기 국회의원의 입법정보 수요예측과 입법정보서비스의 정책적 함의를 찾는 것을 목표로 한다. 입법정보 지원기관인 국회도서관의 참고질의회답을 분석대상으로 하고, 의원의 정치속성과 관계속성을 독립변수로 하여 분석한 결과 소속정당 선출방식 내향중심성에 따라 국회도서관의 입법정보 이용에 유의미한 차이가 있었다. 이와 함께 20대 국회가 여소야대의 국회의원 구성과 3당 체제의 원내구성이라는 점에서 국회도서관의 입법정보 수요가 증가될 것이라고 예측할 수 있었다.

• 보건행정학회지
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• 제18권4호
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• pp.85-110
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• 2008

In this study, we explore the long-term demand forecasting of high-price medical equipments based on logistic and Bass diffusion model. We analyze the specific pattern of each equipment's diffusion curve by interpreting the parameter estimates of Bass diffusion model. Our findings are as follows. First, ultrasonic imaging system, CT are in the stage of maturity and so, the future demands of them are not too large. Second, medical image processing unit is between growth stage and maturity stage and so, the demand is expected to increase considerably for two or three years. Third, MRI is in the stage of take-off and Mammmography X-ray system is in the stage of maturity but, estimates of the potential number of adopters based on logistic model is considerably different to that based on Bass diffusion model. It means that additional data for these two equipments should be collected and analyzed to obtain the reliable estimates of their demands. Fourth, medical image processing unit have the largest q value. It means that the word-of-mouth effect is important in the diffusion of this equipment. Fifth, for MRI and Ultrasonic system, q/p values have the relatively large value. It means that collective power has an important role in adopting these two equipments.