• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2008.04a
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• pp.193-198
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• 2008

• 수도
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• s.2
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• pp.32-39
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• 1974

공공수요의 적정한 예측만이 공급계획에 차질 없는 적정한 생산시설이 가능하므로 대단위화하여 가는 급수수요에서도 그 적정한 예측이 선행되어야 하겠다. 본 논문은 필자의 서울대학교 환경대학원 제1회 졸업논문을 간추린 것으로 제1호에 이어 게재한다.

• Journal of Korea Port Economic Association
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• v.37 no.3
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• pp.1-17
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• 2021

Forecasting the daily volume of container is important in many aspects of port operation. In this article, we utilized a machine-learning algorithm based on decision tree to predict future container throughput of Busan port. Accurate volume forecasting improves operational efficiency and service levels by reducing costs and shipowner latency. We showed that our method is capable of accurately and reliably predicting container throughput in short-term(days). Forecasting accuracy was improved by more than 22% over time series methods(ARIMA). We also demonstrated that the current method is assumption-free and not prone to human bias. We expect that such method could be useful in a broad range of fields.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.8
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• pp.1019-1023
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• 2018

In this paper sensitivity analysis of temperature on special day electricity demand of land and Jeju Island is performed. The basic electricity demand per 3 hours is defined as electricity demand that reflects the GDP effect without the temperature influence. The temperature sensitivity per 3 hours is calculated through the relationship between special day electricity demand normalized to basic electricity demand and temperature. In the future, forecast error will be improved if the temperature sensitivity per 3 hours is applied to the special day load forecasting.

• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.113-124
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• 2015

The KOTI(Korea Transport Institute) released the new version of KTDB(Korea Transport DataBase) in public. The new KTDB is different from the past KTDB in using the concept of trip generation and trip attraction instead of using the concept of Origin-Destination (OD), which was used in the past KTDB. Thus, the appropriate analysis method for future travel demand became necessary for the new type of KTDB. The method should be based on the concept of PA(Production-Attraction). This study focused on analysis of trip generation and trip distribution related to newly generated trips by future land developments. The study also described clearly the standardized forecasting process and methods with PA travel tables. The study showed that the analysis results with OD-based analysis can be different from the results with PA-based analysis in forecasting travel demand for a simple example case even though they used exactly same orignal travel data. Therefore, this study emphasized that a proper method should be applied with the new PA-based KTDB. It is necessary to prepare and disseminate guidelines of the proper forecasting method and application with PA-based travel data for practician.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.1
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• pp.74-82
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• 2011

The Bass model is a cornerstone in diffusion theory which is used for forecasting demand of durables or new services. Three well-known estimation methods for parameters of the Bass model are Ordinary Least Square (OLS), Maximum Likelihood Estimator (MLE), Nonlinear Least Square (NLS). In this paper, a hybrid method incorporating OLS and NLS is presented and it's performance is analyzed and compared with OLS and NLS by using simulation data and empirical data. The results show that NLS has the best performance in terms of accuracy and our hybrid method has the best performance in terms of stability. Specifically, hybrid method has better performance with less data. This result means much in practical aspect because the avaliable data is little when a diffusion model is used for forecasting demand of a new product.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.190-194
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• 2007

In most countries, mobile subscribers are already experiencing 3G-like services. At the moment of launching 3G services, lots of studies showed estimates of the number of subscribers for 3G services, using long-term demand curves, econometric methods or survey methodologies. Those studies mainly focused on the potential number of subscribers and the point of rapid growth rather than precise estimates for the services. Even though we've already experienced parts of 3G services, full length of 3G services are expecting in near future. Therefore, now we need to have more accurate estimates for 3G services. While we thought that 3G services were moved from 2G, in real place 3G services are being evolved from 2G services. In the process of evolving, regulators' policy affects service demand and diffusion significantly. For the more accurate estimates, we need to consider policy issues which influence service diffusion practically in real place. This study aims to present a model which shows better estimates for 3G services with consideration on policy issues, such as numbering issues, price regulation, and competition policy. The consideration can provide more accurate estimates for 3G services with service providers. The methodology could help academicians In forecasting of similar telecommunications services as well.

• Korean Management Science Review
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• v.32 no.4
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• pp.209-236
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• 2015

This study focuses on the network externality effect related to the platform supplementary services. This study designs the network externality of platform and suggests a supplementary service adoption model. Additionally, this study examines the moderating effect of demand forecasting for the platform. Using AMOS program, a structural equation modeling has been used to analyze the research model. The findings can be summarized as follows : First, we find out the structural relationship among the factors (usefulness, perceived value, purchase intention) affecting adoption of the supplementary services. Second, positive perception of platform flow can promote the platform interaction. Third, positive perception of present users based on platform can arouse friendly evaluation in the platform interaction. Fourth, loyalty to the platform brand can improve the perceived usefulness of supplementary services, but cannot lessen the resistance to supplementary service cost. In addition, the moderating effects of demand forecasting for the platform in the path leading from platform factors to supplementary service factors were identified. In conclusion, traditional brand strategy may be effective in platform marketing activities but the extent of performance in the strategy can appear to be quite different. Therefore, taking the relationship with network externality into consideration should be involved in the marketing strategy in platform.

• Korean System Dynamics Review
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• v.3 no.1
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• pp.79-104
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• 2002

A system dynamics project is going on for forecasting automobile market in Korea. The project is made up of three stages, and the first stage has been wrapped up. As the first attempt, most efforts have been focused on the sound foundation rather than the exact forecast. The model consists of three sectors; the supply sector, the demand sector, and the population sector. The supply sector is a simple stock and flow diagrams representing the supply capacities of all automobile types. The major effort is made on the demand sector and the population sector. The demands are divided into three categories; replacement demands, new demands, and additional demands. The model applies “one car per person" concept, and assumes there will be no additional demands for a while. The replacement demands are calculated based on a simple stock and flow diagram. The new demands are calculated via Bass models; each bass model represents a diffusion for each age group. The population is divided into 101 age groups (age 0 to age 100). The model has been calibrated with past 10 year data (1990 - 1999), and tested for the next two years (2000-2001). The results ware acceptable, although a fine tuning is required. Now the second stage is going on, and most of efforts are made how to incorporate the economic and cultural factors.

• International Journal of Highway Engineering
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• v.12 no.2
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• pp.1-7
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• 2010

This study deals with the unsignalized intersection delay in the urban transportation demand forecasting. The objectives are to develop the unsignalized intersection delay models and to comparatively analyze the applicability of the above models. In pursuing the above, this study gives particular attentions to simulating by KHCS program and implementing the case study of Cheongju using EMME/2. The major findings are the followings. First, the 8 unsignalized intersection delay models were developed through 480 simulating results, which are all statistically significant. Second, the estimates by the unsignalized delay models were analyzed to be most fitted to the observed traffic volume data.