E-viri
Recenzirano
Odprti dostop
-
Dorokhov, A S; Kataev, Yu V; Tishaninov, I A; Gradov, E A
Journal of physics. Conference series, 12/2022, Letnik: 2373, Številka: 7Journal Article
Abstract The paper provides information on the causes of failures in automotive equipment and shows the ways to determine failures using digital technologies introduced into the diagnostic process. The implementation of forecasting as a separate stage in the process of diagnosing automotive equipment using machine learning technologies in the form of neural networks is analyzed. The results of the study reflect that the neural network while analyzing a huge amount of data received during remote diagnostics is able to more reliably predict failures of automotive equipment.
