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REFERENCES                                  225
                          gitudinal motion of the maneuverable aircraft             REFERENCES
                          are RMSE V = 0.0026 m/sec, RMSE α = 0.183 deg,
                          RMSE q = 0.0071 deg/sec.                      [1] Egorchev MV, Kozlov DS, Tiumentsev YV. Neural net-
                            The identification of the accuracy of the aero-  work adaptive semi-empirical models for aircraft con-
                                                                          trolled motion. In: 29th Congress of the International
                          dynamical coefficients C x , C z ,and C m is demon-  Council of the Aeronautical Sciences; 2014.
                          strated by the data shown in Figs. 6.13, 6.14,and  [2] Egorchev MV, Tiumentsev YV. Learning of semi-
                          6.15.                                           empirical neural network model of aircraft three-
                            In each of these figures, the upper part of the  axis rotational motion. Opt Memory Neural Netw
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                          figure shows the actual values (according to the  S1060992X15030042.
                          data from [20,21]) of the required coefficients de-  [3] Egorchev MV, Kozlov DS, Tiumentsev YV, Cherny-
                          pending on the angle of attack α and the de-    shev AV. Neural network based semi-empirical mod-
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                          the corresponding ANN modules. We can see       dynamic model identification: A semi-empirical neu-
                          that the accuracy achieved is very high.        ral network based approach. Her Mosc Aviat Inst
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                            The results presented above allow us to draw
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                          the following conclusions.
                                                                          empirical modeling of the longitudinal motion for ma-
                            Just as in the case described in the previous  neuverable aircraft and identification of its aerody-
                          section and in [1,2] for the identification problem  namic characteristics. Studies in computational intelli-
                          of the aerodynamic coefficients C y , C z , C l , C n ,  gence, vol. 736. Springer Nature; 2018. p. 65–71.
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