No AccessA Neural Network Model to Estimate Aircraft Fuel ConsumptionAntonio Trani, F. Wing-Ho, Glen Schilling, Hojong Baik and Anand SeshadriAntonio TraniVirginia TechSearch for more papers by this author, F. Wing-HoRicondo AssociatesSearch for more papers by this author, Glen SchillingNew York DOTSearch for more papers by this author, Hojong BaikVirginia TechSearch for more papers by this author and Anand SeshadriVirginia TechSearch for more papers by this authorSession: ATIO-23: Modeling & Simulation IPublished Online:19 Jun 2012https://doi.org/10.2514/6.2004-6401SectionsRead Now ToolsAdd to favoritesDownload citationTrack citations ShareShare onFacebookXLinked InRedditEmail About Previous chapter Next chapter FiguresReferencesRelatedDetailsSee PDF for referencesCited byPREDICTION OF NOx AND FUEL FLOW OF COMMERCIAL HIGH BYPASS AIRCRAFT ENGINES BASED ON CSA-SVR MODEL27 December 2024 | Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, Vol. 25, No. 4Inteligencia artificial en las operaciones aéreas22 November 2024 | Ciencia y Poder Aéreo, Vol. 20, No. 1A Mathematical Model for the Analysis of Jet Engine Fuel Consumption During Aircraft Climb and Descent1 May 2024 | IEEE Transactions on Intelligent Transportation Systems, Vol. 25, No. 5Estimation Of Fuel Consumption In Aviation Through Time Series2 Mar 2024Prediction of performance degradation in aircraft engines with fuel flow parameter27 November 2023 | Neural Computing and Applications, Vol. 36, No. 6Testing of Aircraft Failure using Machine Learning Algorithms14 Sep 2023Detailed Analysis of Aircraft Fuel Flow Using Data from Flight Data Recorder25 January 2023 | Transportation Research Record: Journal of the Transportation Research Board, Vol. 2677, No. 6A new proposal for the prediction of an aircraft engine fuel consumption: a novel CNN-BiLSTM deep neural network model7 March 2023 | Aircraft Engineering and Aerospace Technology, Vol. 95, No. 5Air traffic flow management under emission policies: Analyzing the impact of sustainable aviation fuel and different carbon prices1 Dec 2022 | Transportation Research Part A: Policy and Practice, Vol. 166Overview of Application in Data Mining Techniques to QAR Data Ansys1 Aug 2022A Mathematical Model for the Analysis of Jet Engine Fuel Consumption during Aircraft Take-off5 Mar 2022A Study on Sustainable Consumption of Fuel—An Estimation Method of Aircraft12 November 2021 | Energies, Vol. 14, No. 22Hierarchical integrated machine learning model for predicting flight departure delays and duration in series1 Aug 2021 | Transportation Research Part C: Emerging Technologies, Vol. 129Deep Learning in Aircraft Design, Dynamics, and Control: Review and Prospects1 Aug 2021 | IEEE Transactions on Aerospace and Electronic Systems, Vol. 57, No. 4A Mathematical Model for the Analysis of Jet Engine Fuel Consumption during Aircraft Cruise18 June 2021 | Energies, Vol. 14, No. 12Predicting the fuel flow rate of commercial aircraft via multilayer perceptron, radial basis function and ANFIS artificial neural networks19 October 2020 | The Aeronautical Journal, Vol. 125, No. 1285Flight performance analysis with data-driven mission parameterization: mapping flight operational data to aircraft performance analysis1 Dec 2020 | Transportation Engineering, Vol. 2The Analyses of Aircraft Performance during Takeoff and Landing with Aerodynamic Interference Effects and the 6-DOF ModelSukru A. 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Chati and Hamsa Balakrishnan8 August 2013 What's Popular AIAA 4th Aviation Technology, Integration and Operations (ATIO) Forum 20 September 2004 - 22 September 2004Chicago, Illinoishttps://doi.org/10.2514/6.2004-6401 Crossmark TopicsAerodromesAerodynamicsAeronauticsAerospace SciencesAir Traffic ControlAir Traffic ManagementAirfieldsAirport AuthorityAirportsAirspaceAviationAviation Authorities and OrganizationsCivil Aviation KeywordsFuel ConsumptionArtificial Neural NetworkHigh Performance AircraftAircraft PerformanceAirspaceTurbopropAirfieldsMach NumbersFederal Aviation AdministrationNational Airspace SystemDigital Topics Aviation Technology, Integration, and Operations