Quality Control of a Real-Time Flight Experiment Using Neural Networks

Authors

  • Vasiliy Akhrameev Moscow Institute of Physics and Technology, Moscow, Russia
  • Eugeniy Tsvetkov Moscow Institute of Physics and Technology, Moscow, Russia
  • Alexander Paschenko V.A. Trapeznikov Institute of Control Sciences of RAS, Moscow, Russia

DOI:

https://doi.org/10.25728/assa.2023.23.3.1370

Keywords:

automatic processing of flight information, test modes, flight experiment, multilayer perceptron, Kohonen network

Abstract

The paper presents some investigations on automatic processing of flight information. The aim of this investigation is to reduce the cost and timing required for aviation equipment testing. The algorithms are developed for recognizing various test modes as well as evaluating the correctness of their implementation. While developing the algorithms a multilayer perceptron and a Kohonen network were used as basics. The results of experiments are presented when applying these algorithms for real testing process.

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Published

2023-10-12

How to Cite

Akhrameev, V., Tsvetkov, E., & Paschenko, A. (2023). Quality Control of a Real-Time Flight Experiment Using Neural Networks. Advances in Systems Science and Applications, 23(3), 127–138. https://doi.org/10.25728/assa.2023.23.3.1370

Issue

Vol. 23 No. 3 (2023): Advances in Systems Science and Applications

Section

Articles