ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 3 No. 1-2 (2018): TTTP - APEIRON

Damir M. Zaborski, Zoran Ž. Avramović

Design and Development of Comprehensive Railway Informationand Communication Systems

Original scientific paper

DOI: 10.7251/JTTTP1801005Z

Abstract

Successful operation of the railways as a large technological system is directly related to the
reliable and timely transmission of data and information. Therefore, the role of the information and communication system (ICS) has irreplaceable importance for operation and functioning of the railways. Considering that the railway modernization represents an uninterrupted process, it is necessary to ensure constant technical and technological development and application of the latest achievements in the field
of information and communication systems. The railway ICS, among other things, provides infrastructure
for the automatic control systems, traffic management and control, monitoring and navigation systems,
data processing devices, and it also provides support to other subsystems designed for safe and consistent
use of the line, as well as efficient management of the modern rail transportation system.

Keywords : railways, transmission data and information, information and communication system, railway ICS.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.