Analysis and forecasting of port logistics using TEI@I methodology

This paper presents an integrated forecasting model based on the TEI@I methodology for forecasting demand for port logistics services – specifically, port container throughput. The model analyzes port logistics time series data and other information in several steps. In the first step, several econometric models are built to forecast the linear segment of port logistics time series. In the second step, a radial basis function neural network is developed to predict the nonlinear segment of the time series. In the third step, the event-study method and expert system techniques are applied to evaluate the effects of economic and other events that may impact demand for port logistics. In the final step, synthetic forecasting results are obtained, based on the integration of predictions from the above three steps. For an illustration, Hong Kong port's container throughput series is used as a case study. The empirical results show the effectiveness of the TEI@I integrated model for port logistics forecasting.

• Record URL:
  • https://doi.org/10.1080/03081060.2013.851506
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/1767712
• Supplemental Notes:
  • Abstract reprinted with permission from Taylor & Francis
• Authors:
  • Tian, Xin
  • Liu, Liming
  • Lai, K K
  • Wang, Shouyang
• Publication Date: 2013-12

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 685-702
• Serial:
  • Transportation Planning and Technology
  • Volume: 36
  • Issue Number: 8
  • Publisher: Taylor & Francis
  • ISSN: 0308-1060
  • Serial URL: https://www.tandfonline.com/toc/gtpt20/current

Subject/Index Terms

• TRT Terms: Case studies; Econometric models; Forecasting; Logistics; Neural networks; Ports; Time series
• Geographic Terms: Hong Kong (China)
• Subject Areas: Freight Transportation; Marine Transportation; Planning and Forecasting; Terminals and Facilities; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01502186
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 23 2013 10:38AM