Experimental Testing of Using the Artificial Neural Networks in Diagnostic Systems for Assessing and Predicting the Technical Condition of Rotorcraft Units

Author:

Bel’skii A. B.,Esipovich O. A.,Safoklov B. B.

Publisher

Allerton Press

Reference21 articles.

1. Belskii, A.B., Promising Research and Innovative Developments for New Helicopter Technology, Fotonika, 2013, no. 4, pp. 66–74.

2. Bel’skii, A.B., Efremov, A.A., and Sizov, A.V., Analysis of Trends and Aspects for Improving the Helicopter Fleet Model Range of the Main Transport Companies in the Russian Federation in Mid-Term and Long-Term Plans, Kachestvo i Zhizn’, 2023, no. 2 (38), pp. 50–59.

3. Serebryansky, S. and Shkurin, M., Predictive Assessment of the Development of Unmanned Aviation System, Journal of Engineering Science and Technology Review, 2022, vol. 15, issue 6, pp. 149–154.

4. Bel’skii, A.B. and Resinets, A.I., Systematization of Approaches for a Comprehensive Solution to the Problem of Improving the Safety of Helicopter Flights, Kachestvo i Zhizn’, 2022, no. 2, pp. 82–90.

5. Dolgov, O.S., Safoklov, B.B., and Smagin, A.A., Diagnostics and Forecasting of the Resource of Take-Off and Landing Devices Using Artificial Neural Networks, Izv. Vuz. Av. Tekhnika, 2022, vol. 65, no. 2, pp. 3–10 [Russian Aeronautics (Engl. Transl.), vol. 65, no. 2, pp. 225–234].

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