Prva međunarodna naučna konferencija

BEZBJEDNO

URBANO

MOBILNO

Vol. 3 No. 2 (2013): JITA - APEIRON

Muzafer H Saračević, Predrag S Stanimirović, Sead H Mašović

Object-Oriented Analysis and Design for one Algorithm of Computational Geometry: Forward, Reverse and Round-Trip Engineering

Original scientific paper

DOI: https://doi.org/10.7251/JIT1302096S

Abstract

Triangulation of the polygon is a fundamental algorithm in computational geometry. This paper considers techniques of object-oriented analysis and design as a new tool for solving and analyzing convex polygon triangulation. The triangulation is analyzed from three aspects: forward, reverse and round-trip engineering. We give a suggestion for improving the obtained software solution of the polygon triangulation algorithm using technique that combines UML modeling and Java programming.

Keywords: Software engineering, Computational geometry, Triangulation of Polygons, Modeling in UML, Java.

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.