Abstract
The problem of the approximate dynamic system attainability domain boundary construction is considered. Results of neural network-based methods efficiency research for the highly-maneuverable aircraft attainability domain boundaries approximate construction are presented.
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Voronov, E.M. and Karpunin, A.A., Algoritm ocenki granic oblasti dostizhimosti letatel’nogo apparata s uchetom tjagi, Vestnik MGTU im. N.Je. Baumana, Ser. “Priborostroenie”, 2007, no. 4 (69), pp. 81–99.
Gurman, V.I., Kvokov, V.I., and Uhin, M.Ju., Priblizhennye metody optimizacii upravlenija letatel’nym apparatom, Avtom. Telemekh., 2008, no. 4, pp. 191–201.
Polyanin, A.D. and Zaitsev, V.F., Handbook of Exact Solutions for Ordinary Differential Equations, 2nd Ed., Boca Raton: Chapman & Hall/CRC Press, 2003.
Fausett, Laurene, Fundamentals of Neural Networks: Architectures, Algorithms, and Applications, London: Prentice-Hall, 1994.
Hagan, M. and Menhaj, M.B., Training Feedforward Networks with the Marquardt Algorithm, IEEE Trans. Neural Networks, 1994, no. 5, pp. 989–993.
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Voronov, E.M., Karpenko, A.P., Kozlova, O.G. et al. Neural network-based approximation of aircraft attainability boundary. Opt. Mem. Neural Networks 19, 291–299 (2010). https://doi.org/10.3103/S1060992X10040065
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DOI: https://doi.org/10.3103/S1060992X10040065