DRONLARDAGI ALOQA XAVFSIZLIGINI TA’MINLASHDA MASHINALI O‘QITISH ALGORITMLARIDAN FOYDALANISHNING SAMARADORLIGI.

Authors

  • Rivojiddinov D.B.
    Turan International University
  • Qurbanov B.B.
    Turan International University
  • Axmedov A.G
    Turan International University

Abstract

Mazkur maqolada dronlardagi aloqa xavfsizligini ta’minlashda mashinali o‘qitish algoritmlari SVM, CNN ML , RNN, CRNN yordamida dronni aniqlash. LSTM UAVlar yordamida nosozliklarni aniqlash va UAV ma’lumotlarini tiklash va axborot xavfsizligini ta’minlashni tahlil qilingan.

Keywords:

ML, UAV, drone, SVM, CNN, RNN, CRNN, LSTM.\

References

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T. Zeng, O. Semiari, M. Mozaffari, M. Chen, W. Saad, and M. Bennis, “Federated learning in the sky: Joint power allocation and scheduling with uav swarms,” in ICC 2020 - 2020 IEEE International Conference on Communications (ICC), 2020, pp. 1–6.

N. Jeong, H. Hwang, and E. T. Matson, “Evaluation of low-cost lidarvsensor for application in indoor uav navigation,” in 2018 IEEE SensorsvApplications Symposium (SAS). IEEE, 2018, pp. 1–5.

Published

How to Cite

Rivojiddinov D.B., R. D., Qurbanov B.B., Q. B., & Axmedov A.G, A. A. (2024). DRONLARDAGI ALOQA XAVFSIZLIGINI TA’MINLASHDA MASHINALI O‘QITISH ALGORITMLARIDAN FOYDALANISHNING SAMARADORLIGI. Universal International Scientific Journal, 1(7), 578–584. Retrieved from https://universaljurnal.uz/index.php/jurnal/article/view/958