IDEAS home Printed from
   My bibliography  Save this article

Applying intelligent methods in detecting maritime smuggling


  • Chih-Hao Wen

    (Department of Logistics Management, National Defense University)

  • Ping-Yu Hsu

    (Department of Business Administration, National Central University)

  • Ming-Shien Cheng

    (Department of Business Administration, National Central University
    Department of Industrial Engineering and Management, Ming Chi University of Technology)


Abstract Taiwan is an island state characterized by well-developed maritime traffic and sea transportation. Smuggling by sea increasingly threatens the country’s social and internal security. The Coast Guard Administration is the main actor intercepting smuggling. This study applies classification trees and Bayesian network algorithms to create dependent and independent classification tree models and Bayesian network models for improving the smuggling vessel recognition rates. We focus on relationships of dependence among smuggled goods (for example, fishery goods, firearms and drugs) and variables (such as information on the home port, the age of boat owners, as well as the arrival and departure dates of vessels). The paper presents a selection method for vessels which could be applicable in a number of other maritime instances, such as, for instance, Port State Control inspection. Our findings help in improving recognition accuracy and reduce the potential harm to social and national security by facilitating the identification of vessels with the largest smuggling value.

Suggested Citation

  • Chih-Hao Wen & Ping-Yu Hsu & Ming-Shien Cheng, 2017. "Applying intelligent methods in detecting maritime smuggling," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 573-599, August.
  • Handle: RePEc:pal:marecl:v:19:y:2017:i:3:d:10.1057_mel.2016.3
    DOI: 10.1057/mel.2016.3

    Download full text from publisher

    File URL:
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

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

    References listed on IDEAS

    1. Farzanegan, Mohammad Reza, 2009. "Illegal trade in the Iranian economy: Evidence from a structural model," European Journal of Political Economy, Elsevier, vol. 25(4), pages 489-507, December.
    2. Andreas Buehn & Mohammad Reza Farzanegan, 2012. "Smuggling around the world: evidence from a structural equation model," Applied Economics, Taylor & Francis Journals, vol. 44(23), pages 3047-3064, August.
    3. Sevim, Cuneyt & Oztekin, Asil & Bali, Ozkan & Gumus, Serkan & Guresen, Erkam, 2014. "Developing an early warning system to predict currency crises," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1095-1104.
    Full references (including those not matched with items on IDEAS)


    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:pal:marecl:v:19:y:2017:i:3:d:10.1057_mel.2016.3. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.