• Journal of the Korean Society for Railway
• /
• v.17 no.4
• /
• pp.307-312
• /
• 2014

This study suggested the ARIMA model taking into consideration the seasonal characteristic factor as a method for efficiently forecasting passenger transport demand of the Joongang Line. The forecasting model was built including the demand for the central inland region tourist train (O-train, V-train), which was opened to traffic in April-, 2013 and run in order to reflect the recent demand for the tourism industry. By using the monthly time series data (103) from January-, 2005 to July-, 2013, the optimum model was selected. The forecasting results of passenger transport demand of the Joongang Line showed continuous increase. The developed model forecasts the short-term demand of the Joongang Line.

• Electronics and Telecommunications Trends
• /
• v.34 no.3
• /
• pp.106-113
• /
• 2019

Mobile traffic is one of the most important indexes of the growth of the mobile communications market, and it has a close relationship with subscribers' service usage patterns, frequency demand and supply, network management, and information communication policy. The purpose of this paper is to understand mobile data usage in Korea and to suggest the optimal steps for establishing the frequency supply and demand system by researching the traffic trends that reflect the characteristics of radio resources in the mobile communications field. To achieve this goal, attempts were made to increase the possibility of policy use by analyzing and forecasting mobile traffic trends, and to improve the accuracy of the research through the verification of the existing prediction results. The paper ends with a discussion of the necessity of a frequency management system based on data science.

• Communications for Statistical Applications and Methods
• /
• v.19 no.1
• /
• pp.183-192
• /
• 2012

This study analyzes the travel behavior for short-term demand forecasting model of KTX. This research suggests the following. First, the outlier criteria is considered to appropriate twice the standard deviation of the traffic. Second, the result of a homogeneity test using ANOVA analysis has been divided into weekdays(Mon Thu and weekends(Fri Sun). Third, a cluster analysis for O/D pairs using trip frequency, traffic averages and th distance between stations was performed.

• Land and Housing Review
• /
• v.2 no.3
• /
• pp.217-226
• /
• 2011

The Seoul Metropolitan Government is striving to minimize the amount of traffic according to the supply of apartment houses along with the solution of housing shortage for the low income people through high density development near the subway area. Therefore, a stronger policy is necessary to control the traffic of the passenger cars in a subway area for the successful high density development focusing on public transportation, and especially, the estimation of the demand of cars with high reliability is necessary to control the demand of parking such as the limited supply of parking lot. Accordingly, this study developed car ownership forecasting model using Look-up Table among category analyses which are easy to be applied and have high reliability. The estimation method using Look-up-Table is possible to be applied to both measurable and immeasurable types, easy to accumulate data, and features the flexible responding depending on the changes of conditions. This study established Look-up-Table model through the survey of geographical location, the scale of housing, the accessible distance to a subway station and to a bus station, the number of bus routes, and the number of car owned with data regarding 242 blocks in Seoul City as subjects.

• The Journal of the Korea Contents Association
• /
• v.19 no.1
• /
• pp.132-140
• /
• 2019

Recently, many cities around the world introduced and operated shared bicycle system to reduce the traffic and air pollution. Seoul also provides shared bicycle service called as "Ddareungi" since 2015. As the use of shared bicycle increases, the demand for bicycle in each station is also increasing. In addition to the restriction on budget, however, there are managerial issues due to the different demands of each station. Currently, while bicycle rebalancing is used to resolve the huge imbalance of demands among many stations, forecasting uncertain demand at the future is more important problem in practice. In this paper, we develop forecasting model for demand for Seoul shared bicycle using statistical time series analysis and apply our model to the real data. In particular, we apply Holt-Winters method which was used to forecast electricity demand, and perform sensitivity analysis on the parameters that affect on real demand forecasting.

• Journal of Korean Society of Transportation
• /
• v.34 no.5
• /
• pp.476-488
• /
• 2016

This study reviewed factors and causes that affect on reliability and accuracy of transportation demand forecasting. In general, the causes of forecasting errors come from variety and irregularity of trip behaviors, data limitation, data aggregation and model simplification. Theoretical understanding about the inevitable errors will be helpful for reasonable decision making for practical transportation policies. The study especially focused on traffic assignment with the KTDB data, and described the factors and causes of errors by classifying six categories such as (1) errors in input data, (2) errors due to spacial aggregation and representation method of network, (3) errors from representing values for variations of traffic patterns, (4) errors from simplification of traffic flow model, and (5) errors from aggregation of route choice behavior.

• Proceedings of the KSR Conference
• /
• 2008.11b
• /
• pp.638-644
• /
• 2008

Mungyeng line(Jupyung${\sim}$Mungyeng) was closed due to a rapid decrease in demand in 1995. However, as the rail transportation demand is expected to increase with the plan to develop a tourist resort and a traffic network in Mungyeng area, it is required to forecast future demand to meet the change of transportation environment in this region. This study predicts the rail transportation demand and analyzes financial benefit in operator's side in case of reopening this line, based on nation-wide traffic volume data from Korean Transportation Database(KTDB). The results of this research can be applied to not only establishing a train operation plan also improving customer service. Moreover, Korail will have an opportunity to develop new business by linking train service to tourist attractions around the Mungyeng area.

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

• Proceedings of the Korean Society of Disaster Information Conference
• /
• 2023.11a
• /
• pp.259-260
• /
• 2023

The rapid urbanization and modernization observed in countries like Myanmar have led to significant concerns regarding traffic congestion, especially in urban areas. This study focuses on the analysis and revitalization of urban transport in selected areas of Myanmar. The core of urban transportation planning lies in travel forecasting, which employs models to predict future traffic patterns and guide decisions related to road capacity, transit services, and land use policies. Travel demand modeling involves a series of mathematical models that simulate traveler behavior and decision-making within a transportation system, including highways, transit options, and policies. The paper offers an overview of the traditional four-step transportation modeling system, utilizing a simplified transport network in the context of Mandalay City, Myanmar.

• Journal of Intelligence and Information Systems
• /
• v.3 no.1
• /
• pp.31-45
• /
• 1997

To date, research on data mining has focused primarily on individual techniques to su, pp.rt knowledge discovery. However, the integration of elementary learning techniques offers a promising strategy for challenging a, pp.ications such as forecasting nonlinear processes. This paper explores the utility of an integrated a, pp.oach which utilizes a second-order learning process. The a, pp.oach is compared against individual techniques relating to a neural network, case based reasoning, and induction. In the interest of concreteness, the concepts are presented through a case study involving the prediction of network traffic for video-on-demand.