ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 1 No. 1 (2016): TTTP - APEIRON

Dusan Radosavljevic, Marjana Radosavljevic, Pavle Gladovic, Milan Stankovic, Dejan Bogicevic

Financing Public Transportation of Passengers

Original scientific paper

DOI: 10.7251/JTTTP1601025R

Abstract

Public transportation of passengers has very important role in the life and functioning of urban areas. Public transportation of passengers stimulates effective economic activities, improves the life standard and increases the mobility of the population. Such system is difficult for financing. The revenue that the system brings is not sufficient to compensate for the operational costs. This research presents the possible ways of financing the system of public transit. There are various experiences in financing the public transit in European cities, but this problem has been also identified in the cities all over the world. The system of public transit in the Republic of Serbia has recently started to implement activities related to the improvement in the quality of work and services, as well as rationalization of the system in all aspects of business and operation, improvement of organization and maintenance at all levels, and increase in the efficiency and reputation.

Keywords: financing, public transportation of passengers (or public transit).

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.