Artificial neural networks applied to modelling the aircraft descent phase

This paper presents the use of an artificial neural network for modelling the aircraft descent phase. This was achieved by analysing data records from an on-board flight data recorder. In order to determine the influence of the artificial neural network structure on the precision of reproducing the actual flight path, several different network configurations were tested. From the results obtained, those that most accurately reproduced the actual aircraft descent phase were selected. The model created in this way is characterised by high accuracy in reproducing the real object and can be used, among other things, for simulation research on air traffic.Neural network modelling of the descent phase of an aircraft
Abstract
This article discusses the neural network modelling of the descent phase of an aircraft. The model is based on the parameters recorded by the flight data recorder. Several different network configurations were tested to define how the structure of neural network affects the precision of reconstruction of the flight. Created model reconstructs the real operations of the flight precisely and can be used to the simulation research on the air traffic. (…)

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