Decision trees based multi-factor remote technical diagnostics of car retarders

Viktor L. Panasov; Nikolay A. Tseligorov; Nikolay M. Nechitaylo

doi:10.1117/12.2680707

27 April 2023 Decision trees based multi-factor remote technical diagnostics of car retarders

Viktor L. Panasov, Nikolay A. Tseligorov, Nikolay M. Nechitaylo

Proceedings Volume 12637, International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023); 1263703 (2023) https://doi.org/10.1117/12.2680707
Event: International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023), 2023, Fergana, Uzbekistan

Abstract

Modern hump car retarder control systems and their technical diagnostic methods are reviewed. Disadvantages of existing analytical methods of technical diagnostics are revealed. Factors, which help to increase the accuracy of technical diagnostics of car retarders, available in existing hump automated control complexes, are shown. The paper suggests to build a new intelligent technical diagnostic system to improve the accuracy of the current ones. The suggested system will use decision trees, created by means of Data Mining approach under conditions of small training set amount. This approach is based on the ideas of intelligent system self-organization. The increase in accuracy of the decision rules is shown on the verification database examples.

Citation Download Citation

Viktor L. Panasov, Nikolay A. Tseligorov, and Nikolay M. Nechitaylo "Decision trees based multi-factor remote technical diagnostics of car retarders", Proc. SPIE 12637, International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023), 1263703 (27 April 2023); https://doi.org/10.1117/12.2680707

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