The application of neural networks for the life-cycle analysis of road and rail rolling stock during the operational phase

Abstract

The aim of this article is to assess the possibility of using neural networks to analyse the life cycle of rolling stock in the operational phase by selecting the number of rolling stock sets and rail using the example of public transport in the Szczecin agglomeration. The research was conducted in September 2019 and June 2020. It included the number of tram and bus rolling stock sets on individual public transport lines based on data from the Central Public Transport Management System in the Szczecin agglomeration. The research, which was based on comparative analyses of individual types of rolling stock and their technical and economic data, took into account the life-cycle assessment criteria associated with the operation of vehicles in relation to the number of rolling stock sets. The use of neural networks on the example of the city of Szczecin for the purpose of life-cycle analysis, can make a significant contribution to creating a decision model for the improvement of public transport in cities with various types of public transport vehicles.

Properties of WC-Co coatings with Al2O3 addition

“…Highly wear-resistant materials have a very wide range of applications, from biotechnological equipment (Skrzypczak- Skrzypczak-Pietraszek et al, 2019), through intelligent in civil engineering (Piotrowski et al, 2014;Majewski et al, 2020) and classic reinforcement of mechanically (Dwornicka et al, 2017;Radek et al, 2018;Markovic et al, 2021) and thermo-mechanically cooperating machine parts (Orman, 2014;Dabek et al, 2019;Orman et al, 2020), to production engineering (Pacana et al, 2014;Pacana et al, 2019;Pacana et al, 2020). The study of the properties of such reinforced materials is an intense subject of work in materials science (Ulewicz, 2015;Radzyminska-Lenarcik et al, 2018) and inspiration for data analysis methods (Styrylska and Pietraszek, 1992), both classical (Pietraszek et al, 2014) and non-parametric approaches: fuzzy (Pietraszek, 2012), neural-network-based (Pietraszek, 2003;Regulski and Abramek, 2022) and resampling (Pietraszek and Gadek-Moszczak, 2013).…”

Sustainable pricing of tariffs for rolling stock operators: Principles and mathematical analysis

“…Let us give a brief review of papers that are, to one degree or another, devoted to the research of these issues [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16].…”

Numerical Analysis of a Pneumatic Cushion Operation Safety, including the Airflow Conditions

“…The main risk factors for failures are equipment wear [23][24][25], failures of structural joints, including welded joints [26][27][28], and unwanted gas and liquids ingress [29][30][31]. Preventing failures requires the use of materials with desired technological and functional properties [32][33][34], and in specific cases, complementing them with coatings that modify their characteristics [35], including coatings with special functional properties [36][37][38] and those that alter mechanical properties [39][40][41].…”