Abstract Predicting the fuel consumption of transport aircraft is vital for minimizing the detrimental effects of fuel emissions on the environment, saving fuel energy sources, reducing flight costs, achieving more accurate aircraft trajectory prediction, and providing effective and seamless management of air traffic. In this study, a genetic algorithm-optimized neural network topology is designed to predict the fuel flow-rate of a transport aircraft using real flight data. This model incorporates the cruise flight phase and the fuel consumption dependency with respect to both the variation of true airspeed and altitude. Feed-forward backpropagation and Levenberg–Marquardt algorithms are applied, and a genetic algorithm is utilized to design the optimum network architecture regarding time and effort. The predicted fuel flow-rates closely match the real data for both neural network training algorithms. Backpropagation gives the best accuracy for the climb and cruise phases, whereas the Levenberg–Marquardt algorithm is optimal for the descent phase.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Modeling the fuel flow-rate of transport aircraft during flight phases using genetic algorithm-optimized neural networks


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2015-11-23


    Format / Umfang :

    11 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    Modeling Aircraft Wing Loads from Flight Data Using Neural Networks

    Allen, Michael J. / Dibley, Ryan P. | NTRS | 2003



    Modeling Aircraft Wing Loads from Flight Data Using Neural Networks*†

    Allen, Michael J. / Dibley, Ryan P. | SAE Technical Papers | 2003


    Modeling Aircraft Wing Loads from Flight Data Using Neural Networks

    Allen, M. J. / Dibley, R. P. / Society of Automotive Engineers | British Library Conference Proceedings | 2003