IDEAS home Printed from https://ideas.repec.org/a/igg/jirr00/v8y2018i4p51-66.html
   My bibliography  Save this article

A Knowledge Based Approach for Accident Analysis: Application to the Safety of Automated Rail Transport Systems

Author

Listed:
  • Lassad Mejri

    (RIADI Labs, Carthage University, Tunis, Tunisia & JOUF University, Tunis, Tunisia)

Abstract

This article introduces a research aiming at the development of a decision support system concerning the approval of automated railway transportation systems. The objective is to evaluate the degree of compliance of the transportation system according to the security standards by the simulation of the scenarios of accident. To reach this target, the authors envisaged an approach Rex (Return of experience) who draws lessons of accidents lived and/or imagined by the experts of the analysis of security in the NRITS (National Research Institute on Transports and their Security): currently IFSTAAR. The approach consists in offering aid to the experts by a reuse of the accidents already validated. This approach provides to the experts a class of similar accidents situations to the new case. The case-based reasoning is then exploited allowing choosing one under group of historical cases that can help in the resolution of the new case introduced by the experts.

Suggested Citation

  • Lassad Mejri, 2018. "A Knowledge Based Approach for Accident Analysis: Application to the Safety of Automated Rail Transport Systems," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 8(4), pages 51-66, October.
    • Handle: RePEc:igg:jirr00:v:8:y:2018:i:4:p:51-66
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJIRR.2018100104
    Download Restriction: no
    ---><---

    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:igg:jirr00:v:8:y:2018:i:4:p:51-66. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.