MATEC Web Conf.
Volume 216, 2018X International Scientific and Technical Conference “Polytransport Systems”
|Number of page(s)||8|
|Section||Transportation Management and Transport Economy|
|Published online||17 October 2018|
Application of probability and statistics methods in arrangement of railway transportation
Irkutsk State University of Railway Engineering, 634074 Irkutsk, Russia
* Corresponding author: firstname.lastname@example.org
Complex economic and mathematical methods are becoming more widespread in training of specialists in the field of railroad communication arrangement. The purpose of this study is to develop an effective methodology for mathematical training of railway transportation specialists on the basis of active training methods. The article deals with application of probabilistic and statistical methods to problems in design of railway transportation, for example, fluctuations in loading of railway stations and distribution of the time interval between arrival of trains. Using the example of the flow of arriving trains, the technology of testing the hypothesis that the time between arrival of trains is distributed according to the exponential law and the hypothesis of independence of events in the flow is displayed in detail. When confirming each of these hypotheses, it must be concluded that the flow of trains arriving at the station is according to the simplest (Poisson’s) model. This conclusion allows using the apparatus of Markov chains to describe a random process.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.