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Predict Port Throughput Based on Probabilistic Forecast Model

  • Yihan Chen
  • Zhonghua Jin
  • Xuejun LiuEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 699)

Abstract

When the service region of ports overlap, consignors’ selecting behaviors for shipping ports become homogeneous to commuters’ choosing behaviors on trips. The commuters’ travel behaviors can be described through a probabilistic model in transportation planning. In this study, we adopt the transportation probabilistic forecast model to forecast port throughput. First, we amend the model with a port attraction coefficient to forecast port throughput distributions between different ports. Then, forecast for each port throughput is obtained by reallocation of regional total port throughput to each nearby port. We use the port of Fuyang as an empirical research in this paper to validate the methodology. Results compared between this method and traditional regression model indicate that this method provides more persuasive reasoning.

Keywords

Port throughput Probabilistic forecast model Port attraction coefficient Cargo distribution 

Notes

Acknowledgement

This research is funded by the Natural Science Foundation of Hubei [grant number 2014CFB709] and the National Natural Science Foundation of China [grant number 51579182].

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.School of Urban DesignWuhan UniversityWuhan CityChina
  2. 2.Department of Urban Planning and Environmental PolicyTexas Southern UniversityHoustonUSA

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