The aim of the article is the material and economic assessment of the life cycle of city buses with com-bustion engines. As part of the analysis, the analyzed parameters were optimized using neural networks with the use of a regression model. As part of the life cycle assessment criteria, three types of Solaris Urbino buses were analyzed. As a result of the research carried out for buses, the results were obtained regarding the optimal duration of operation, the number and cost of oil, air and fuel filter changes, and the replacement period of buses. The presented research and analyzes have a significant impact on the processes of purchasing and operating city buses.
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