• Title/Summary/Keyword: transportation demand forecasting

Search Result 126, Processing Time 0.024 seconds

Forecasting Market Demand of u-Transportation Vehicle Sensor OBU (u-Transportation UVS 단말기 시장수요예측)

  • Jeong, Eon-Su;Kim, Won-Kyu;Kim, Min-Heon;Kim, Byung-Jong;Kim, Song-Ju
    • Journal of The Institute of Information and Telecommunication Facilities Engineering
    • /
    • v.8 no.4
    • /
    • pp.157-162
    • /
    • 2009
  • This study's purpose is to forecast the market demand of UVS (u-Transportation Vehicle Sensor) OBU (On-board Unit) of the ubiquitous Transportation. Bass model, Logistic model, and Gompertz model were used for the forecasting market demand. Firstly, this research focused on the market size for the u-T OBU. All three models were used for the market size prediction and the average values were used. The Bass model were calibrated and the market demand for the UVS OBU of the u-Transportation system were estimated using this model.

  • PDF

Development of Peak Power Demand Forecasting Model for Special-Day using ELM (ELM을 이용한 특수일 최대 전력수요 예측 모델 개발)

  • Ji, Pyeong-Shik;Lim, Jae-Yoon
    • The Transactions of the Korean Institute of Electrical Engineers P
    • /
    • v.64 no.2
    • /
    • pp.74-78
    • /
    • 2015
  • With the improvement of living standards and economic development, electricity consumption continues to grow. The electricity is a special energy which is hard to store, so its supply must be consistent with the demand. The objective of electricity demand forecasting is to make best use of electricity energy and provide balance between supply and demand. Hence, it is very important work to forecast electricity demand with higher precision. So, various forecasting methods have been developed. They can be divided into five broad categories such as time series models, regression based model, artificial intelligence techniques and fuzzy logic method without considering special-day effects. Electricity demand patterns on holidays can be often idiosyncratic and cause significant forecasting errors. Such effects are known as special-day effects and are recognized as an important issue in determining electricity demand data. In this research, we developed the power demand forecasting method using ELM(Extreme Learning Machine) for special day, particularly, lunar new year and Chuseok holiday.

Forecasting Model of Air Passenger Demand Using System Dynamics (시스템다이내믹스를 이용한 항공여객 수요예측에 관한 연구)

  • Kim, Hyung-Ho;Jeon, Jun-woo;Yeo, Gi-Tae
    • Journal of Digital Convergence
    • /
    • v.16 no.5
    • /
    • pp.137-143
    • /
    • 2018
  • Korea's air passenger traffic has been growing steadily. In this paper, we propose a forecasting model of air passenger demand to ascertain the growth trend of air passenger transportation performance in Korea. We conducted a simulation based on System Dynamics with the demand as a dependent variable, and international oil prices, GDP and exchange rates as exogenous variables. The accuracy of the model was verified using MAPE and $R^2$, and the proposed prediction model was verified as an accurate prediction model. As a result of the demand forecast, it is predicted that the air passenger demand in Korea will continue to grow, and the share of low cost carriers will increase sharply. The addition of the Korean transportation performance of foreign carriers in Korea and the transportation performance of Korean passengers due to the alliance of airlines will provide a more accurate forecast of passenger demand.

A System Dynamics Model for Basic Material Price and Fare Analysis and Forecasting (시스템 시뮬레이션을 통한 원자재 가격 및 운송 운임 모델)

  • Jung, Jae-Heon
    • Korean System Dynamics Review
    • /
    • v.10 no.1
    • /
    • pp.61-76
    • /
    • 2009
  • We try to use system dynamics to forecast the demand/supply and price, also transportation fare for iron ore. Iron ore is very important mineral resource for industrial production. The structure for this system dynamics shows non-linear pattern and we anticipated the system dynamic method will catch this non-linear reality better than the regression analysis. Our model is calibrated and tested for the past 6 year monthly data (2003-2008) and used for next 6 year monthly data(2008-2013) forecasting. The test results show that our system dynamics approach fits the real data with higher accuracy than the regression one. And we have run the simulations for scenarios made by possible future changes in demand or supply and fare related variables. This simulations imply some meaningful price and fare change patterns.

  • PDF

A Study on forecasting of the Transportation Demand Mungyeng Line (문경선 운영 재개에 따른 이용수요 예측 연구)

  • Kim, Ick-Hee;Lee, Kyung-Tae
    • 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.

  • PDF

Exercising The Traditional Four-Step Transportation Model Using Simplified Transport Network of Mandalay City in Myanmar (미얀마 만달레이시의 단순화된 교통망을 이용한 전통적인 4단계 교통 모델에 관한 연구)

  • Wut Yee Lwin;Byoung-Jo Yoon;Sun-Min Lee
    • Journal of the Society of Disaster Information
    • /
    • v.20 no.2
    • /
    • pp.257-269
    • /
    • 2024
  • Purpose: The purpose of this study is to explain the pivotal role of the travel forecasting process in urban transportation planning. This study emphasizes the use of travel forecasting models to anticipate future traffic. Method: This study examines the methodology used in urban travel demand modeling within transportation planning, specifically focusing on the Urban Transportation Modeling System (UTMS). UTMS is designed to predict various aspects of urban transportation, including quantities, temporal patterns, origin-destination pairs, modal preferences, and optimal routes in metropolitan areas. By analyzing UTMS and its operational framework, this research aims to enhance an understanding of contemporary urban travel demand modeling practices and their implications for transportation planning and urban mobility management. Result: The result of this study provides a nuanced understanding of travel dynamics, emphasizing the influence of variables such as average income, household size, and vehicle ownership on travel patterns. Furthermore, the attraction model highlights specific areas of significance, elucidating the role of retail locations, non-retail areas, and other locales in shaping the observed dynamics of transportation. Conclusion: The study methodically addressed urban travel dynamics in a four-ward area, employing a comprehensive modeling approach involving trip generation, attraction, distribution, modal split, and assignment. The findings, such as the prevalence of motorbikes as the primary mode of transportation and the impact of adjusted traffic patterns on reduced travel times, offer valuable insights for urban planners and policymakers in optimizing transportation networks. These insights can inform strategic decisions to enhance efficiency and sustainability in urban mobility planning.

A Quantitative Study on Air Transportation Demand Forecasting in Heuksando (흑산도의 항공수요예측에 관한 정량적 연구)

  • Song, B.H.;Song, Y.K.;Choi, Y.C.
    • Journal of the Korean Society for Aviation and Aeronautics
    • /
    • v.9 no.2
    • /
    • pp.101-111
    • /
    • 2001
  • Heuksando is an island which belongs to Shinangun, Jeonllanamdo and is located on the southwest sea of the Korean peninsula. Around this island, there are many beautiful islands which embroider the archipelago such as Hongdo, Soheuksando, Haeuido, Gageodo. However in the transportation mode we could not offer convenience to all the visitors coming to this area because access to this place can be made only by ship from Mokpo harbor. So new airport is desirable to solve this problem in this area. Therefore, this study is forecasting air transportation demand between Heuksando and several domestic places in order to give the fundamental materials not only to address the appropriateness to construct a new airport but also to determine it's size and necessary facilities.

  • PDF

Application of Risk Management to Forecasting Transportation Demand by Delphi Technique (Delphi기법을 통한 교통수요예측 Risk Management 적용 방안)

  • Chung, Sung-Bong
    • Journal of the Korea Safety Management & Science
    • /
    • v.13 no.2
    • /
    • pp.267-273
    • /
    • 2011
  • Since 'The Act on Private Investment of The Infrastructure' was established in 1994, private investment as well as government's investment in transport infrastructure has been active. However investment in transport infrastructure has more risks than others' due to uncertainty both in traffic volume and in construction cost. In the current appraisal procedure of deciding transportation infrastructure investment, instead of risk management, the sensitivity analysis considering only the changes of benefit, cost and social discount rate which are main factor affecting economic feasibility is carried out. Therefore the uncertainty of various factors affecting demand, cost and benefit are not considered in feasibility study. In this study the problems in current investment appraisal system were reviewed. Using Delphi technique the major factors which have high uncertainty in feasibility study were surveyed and then improvement plan was suggested in the respective of classic 4 step demand forecasting method. The range estimation technique was also mentioned to deal with the uncertainty of the future.