The full text of this article
Data mining in rail transport delay chain analysis
by Jouni Wallander; Miika Mäkitalo
International Journal of Shipping and Transport Logistics (IJSTL), Vol. 4, No. 3, 2012
Abstract: Railway systems face the demand for efficient, reliable, and low-cost logistic services. Nevertheless, in many countries, punctuality of rail traffic plummet at a poor level. Even though high quality is pursued, there seems to be a lack of broad understanding when it comes to the concatenation of delays. However, understanding rail traffic delay chains is important for improving the performance of rail transport quality. Our research uses a data-mining approach for analysing rail transport delay chains, with data from passenger train traffic on the Finnish rail network. This study illustrates data mining is a useful tool for identifying and mapping the delay chains. It may be concluded that based on a deeper understanding of the delay concatenation, it is possible to develop rail traffic punctuality and the whole railway system. In medium and long-term planning, data-mining analyses of rail traffic can help to develop a more robust timetable structures, and provide tools for rail network planning.
Online publication date: Sun, 24-Jun-2012
is only available to individual subscribers or to users at subscribing institutions.
Go to Inderscience Online Journals to access the Full Text of this article.
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Shipping and Transport Logistics (IJSTL):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable).
See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org