FEATURES OF THE USE OF NEURAL NETWORKS IN THE DESIGN OF UAVS FOR FLIGHT IN THE STRATOSPHERE
DOI:
https://doi.org/10.18372/2306-1472.87.15566Keywords:
neural networks, machine learning, power supply, stratospheric UAVs, energy efficiency, battery, solarAbstract
Problems of application of neural networks during UAV design, and also questions of development of methods and algorithms of synthesis of neural network.
References
Babak S.V. (2016). Features of practical use of autonomous diagnostic complexes for thermal control of overhead power lines / SV Babak, MV Myslovych // Technical electrodynamics. № 1. - P.73-80.
Barsov V.I. (2008). The concept of creating a system for processing information of unmanned aerial vehicles based on the use of modular arithmetic / VI Barsov // Elektroinform. № 4. - pp. 9-11.
Belyaev Yu. B. (2003). Modeling of the decision-making process by the operator of the aviation ergatic system in special cases of flight / Yu.B. Belyaev, T.F. Shmelyova, Yu. V. Sikirda // Automation of production processes. № 2 (17). - pp. 17-23.
Bondarev D.I. (2015). System analysis and classification of group flights of unmanned aerial vehicles // XV International scientific-practical conference of young scientists and students "Flight. Modern problems of science ", April 2015: thesis add. - K .: NAU, - pp. 56-61.
Verba V.S., Tatarsky B.G. (2016). Complexes with unmanned aerial vehicles. In 2 books. M.: Radio Engineering,- 1352 p.
Voronovsky G.K., Makhotilo K.V., Petrashev S.N., Sergeev S.A. (1997). Genetic algorithms, artificial neural networks and problems of virtual reality. - Custom. - H .: OSNOVA, - pp. 99-112.
Galushkin A.I. (2010). Theory of neural networks. / А.І. Galushkin - M .: IPRZHR, - 348 p.
Golovkin B.A. (1973). Machine recognition and linear programming. - Moscow: Soviet Radio. - 100 p.
Dakhno N.B. (2015). Models of decision-making for remote control of unmanned aerial vehicles based on variational-gradient methods: author's ref. dis. on zdob. Science. degree of Cand. tech. Science: special. 05.13.06 "Inform. Technologies" / Dakhno Natalia Borysivna; State. University of Telecommunications. – K.,– pp. 2-14.
Deich A.M. (1979). Methods of identification of dynamic objects. - M: Energy, - pp. 117-144.
Zhivotovsky R.M. (2016). Improved method of adaptive control of signal parameters for unmanned aerial vehicles. Control, navigation and communication systems. № 3. - pp. 140-145.
Mesyura V.I., Vakhovskaya L.M. (2000). Fundamentals of designing artificial intelligence systems: Textbook. - Vinnytsia: VSTU, - 96 p.
Polishchuk D.O. (2015). Complex deterministic evaluation of complex hierarchical network systems: I. Description of the method / D.O. Polishchuk, O.D. Polishchuk, M.S. Yadzhak // System research and information technology. № 1.- pp. 21–31.
Rutkovskaya D. (2004). Neural networks, genetic algorithms and fuzzy systems / D. Rutkovskaya, M. Pilinsky, L. Rutkovsky. - M. Hotline -Telecom. - 112 p.
Stratiy A.V. (2015). Consolidation of information flows in air navigation systems // XV International scientific-practical conference of young scientists and students "Flight. Modern problems of science ", April 2015: thesis add. - K.: NAU,. - pp. 90-98.
Shmelyova T.F. (2015). Deterministic models of action of the aircraft crew in case of a special case in flight / T.F. Shmelyova, V.V. Shyshakov, О.V. Shostak // Science and Technology of the Air Force of the Armed Forces of Ukraine. № 2 (19). -pp. 33–37.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
