IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v55y2017i17p5001-5010.html
   My bibliography  Save this article

Using artificial neural networks to predict container flows between the major ports of Asia

Author

Listed:
  • Feng-Ming Tsai
  • Linda J.W. Huang

Abstract

Container flow information is a critical issue for port operators and liners to support their strategic planning and decision-making. This study uses artificial neural networks (ANNs) to predict container flows by considering GDP, interest rates, the value of export and import trade, the numbers of export and import containers and the number of quay cranes. ANNs are developed for data mining purposes, and the developed model can simultaneously predict container flows between the major ports of Asia. The forecasting results indicate that the prediction errors are relatively small in most selected ports, and thus shipping companies can use the container flow prediction model to make decisions concerning operations. The results can be further applied to the trend analysis of container flows among the major ports of Asia, and a community analysis of the containers was conducted for the purpose of supply chain management.

Suggested Citation

  • Feng-Ming Tsai & Linda J.W. Huang, 2017. "Using artificial neural networks to predict container flows between the major ports of Asia," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5001-5010, September.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:17:p:5001-5010
    DOI: 10.1080/00207543.2015.1112046
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2015.1112046
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2015.1112046?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Coto-Millán, Pablo & Baños-Pino, José & Castro, José Villaverde, 2005. "Determinants of the demand for maritime imports and exports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 41(4), pages 357-372, July.
    2. Wang, Shuaian & Meng, Qiang & Bell, Michael G.H., 2013. "Liner ship route capacity utilization estimation with a bounded polyhedral container shipment demand pattern," Transportation Research Part B: Methodological, Elsevier, vol. 47(C), pages 57-76.
    3. Jones, Dean A. & Farkas, Julie L. & Bernstein, Orr & Davis, Chad E. & Turk, Adam & Turnquist, Mark A. & Nozick, Linda K. & Levine, Brian & Rawls, Carmen G. & Ostrowski, Scott D. & Sawaya, William, 2011. "U.S. import/export container flow modeling and disruption analysis," Research in Transportation Economics, Elsevier, vol. 32(1), pages 3-14.
    4. Santos, Noe I. & Said, Aly M. & James, David E. & Venkatesh, Nanda H., 2012. "Modeling solar still production using local weather data and artificial neural networks," Renewable Energy, Elsevier, vol. 40(1), pages 71-79.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jin, Jiahuan & Ma, Mingyu & Jin, Huan & Cui, Tianxiang & Bai, Ruibin, 2023. "Container terminal daily gate in and gate out forecasting using machine learning methods," Transport Policy, Elsevier, vol. 132(C), pages 163-174.
    2. Huang, Dong & Grifoll, Manel & Sanchez-Espigares, Jose A. & Zheng, Pengjun & Feng, Hongxiang, 2022. "Hybrid approaches for container traffic forecasting in the context of anomalous events: The case of the Yangtze River Delta region in the COVID-19 pandemic," Transport Policy, Elsevier, vol. 128(C), pages 1-12.
    3. Christoph Martius & Lutz Kretschmann & Miriam Zacharias & Carlos Jahn & Ole John, 2022. "Forecasting worldwide empty container availability with machine learning techniques," Journal of Shipping and Trade, Springer, vol. 7(1), pages 1-24, December.
    4. Yi Xiao & Minghu Xie & Yi Hu & Ming Yi, 2023. "Effective multi‐step ahead container throughput forecasting under the complex context," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1823-1843, November.
    5. Feng, Hongxiang & Grifoll, Manel & Zheng, Pengjun, 2019. "From a feeder port to a hub port: The evolution pathways, dynamics and perspectives of Ningbo-Zhoushan port (China)," Transport Policy, Elsevier, vol. 76(C), pages 21-35.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Shuaian, 2015. "Optimal sequence of container ships in a string," European Journal of Operational Research, Elsevier, vol. 246(3), pages 850-857.
    2. Yi Xiao & Shouyang Wang & Ming Xiao & Jin Xiao & Yi Hu, 2017. "The Analysis for the Cargo Volume with Hybrid Discrete Wavelet Modeling," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 851-863, May.
    3. Chen, Rui & Meng, Qiang & Jia, Peng, 2022. "Container port drayage operations and management: Past and future," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    4. Wang, Shuaian, 2013. "Essential elements in tactical planning models for container liner shipping," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 84-99.
    5. Marco Ferretti & Ugo Fiore & Francesca Perla & Marcello Risitano & Salvatore Scognamiglio, 2022. "Deep Learning Forecasting for Supporting Terminal Operators in Port Business Development," Future Internet, MDPI, vol. 14(8), pages 1-19, July.
    6. César Ducruet & Hidekazu Itoh, 2022. "Spatial Network Analysis of Container Port Operations: The Case of Ship Turnaround Times," Networks and Spatial Economics, Springer, vol. 22(4), pages 883-902, December.
    7. Rao K, D.V. Siva Krishna & Premalatha, M. & Naveen, C., 2018. "Analysis of different combinations of meteorological parameters in predicting the horizontal global solar radiation with ANN approach: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 248-258.
    8. Qiang Meng & Shuaian Wang & Henrik Andersson & Kristian Thun, 2014. "Containership Routing and Scheduling in Liner Shipping: Overview and Future Research Directions," Transportation Science, INFORMS, vol. 48(2), pages 265-280, May.
    9. Paula C. Pereda & Andrea Lucchesi, 2022. "Alternative frameworks for cost-effectiveness analysis of environmental policies in maritime transport," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(3), pages 630-650, September.
    10. César Ducruet & Hidekazu Itoh, 2022. "Spatial network analysis of container port operations: the case of ship turnaround times," EconomiX Working Papers 2022-15, University of Paris Nanterre, EconomiX.
    11. Manuel Herrera & Per J. Agrell & Casiano Manrique-de-Lara-Peñate & Lourdes Trujillo, 2017. "Vessel capacity restrictions in the fleet deployment problem: an application to the Panama Canal," Annals of Operations Research, Springer, vol. 253(2), pages 845-869, June.
    12. Mousa, Hasan & Gujarathi, Ashish M., 2016. "Modeling and analysis the productivity of solar desalination units with phase change materials," Renewable Energy, Elsevier, vol. 95(C), pages 225-232.
    13. Lai, Xiaofan & Wu, Lingxiao & Wang, Kai & Wang, Fan, 2022. "Robust ship fleet deployment with shipping revenue management," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 169-196.
    14. Chi, Junwook, 2016. "Exchange rate and transport cost sensitivities of bilateral freight flows between the US and China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 1-13.
    15. Xing, Hui & Spence, Stephen & Chen, Hua, 2020. "A comprehensive review on countermeasures for CO2 emissions from ships," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    16. Likun Wang & Anne Goodchild & Yong Wang, 2018. "The effect of distance on cargo flows: a case study of Chinese imports and their hinterland destinations," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(3), pages 456-475, September.
    17. Wang, Shuaian & Meng, Qiang, 2013. "Reversing port rotation directions in a container liner shipping network," Transportation Research Part B: Methodological, Elsevier, vol. 50(C), pages 61-73.
    18. Ng, ManWo, 2014. "Distribution-free vessel deployment for liner shipping," European Journal of Operational Research, Elsevier, vol. 238(3), pages 858-862.
    19. Chen, Kang & Chen, Dongxu & Sun, Xueshan & Yang, Zhongzhen, 2016. "Container Ocean-transportation System Design with the factors of demand fluctuation and choice inertia of shippers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 267-281.
    20. Ching-Chih Chou & Chien-Wen Shen & Dapeng Gao & Yang Gao & Kai Wang & Sang-Bing Tsai, 2018. "Modelling the Dynamic Impacts of High Speed Rail Operation on Regional Public Transport—From the Perspective of Energy Economy," Energies, MDPI, vol. 11(5), pages 1-15, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:55:y:2017:i:17:p:5001-5010. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.