a hybrid original approach for prediction of the aerodynamic coefficients of an atr-42 scaled wing model

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2016
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Abstract
A new approach for the prediction of lift, drag, and moment coefficients is presented. This approach is based on the support vector machines (SVMs) methodology and an optimization meta-heuristic algorithm called extended great deluge (EGD). The novelty of this approach is the hybridization between the SVM and the EGD algorithm. The EGD is used to optimize the SVM parameters. The training and validation of this new identification approach is realized using the aerodynamic coefficients of an ATR-42 wing model. The aerodynamic coefficients data are obtained with the XFoil software and experimental tests using the Price–Païdoussis wind tunnel. The predicted results with our approach are compared with those from the XFoil software and experimental results for different flight cases of angles of attack and Mach numbers. The main purpose of this methodology is to rapidly predict aircraft aerodynamic coefficients.
Reference Key
mosbah2016chinesea Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Abdallah Ben Mosbah;Ruxandra Mihaela Botez;Thien My Dao
Journal Cancer epidemiology
Year 2016
DOI
10.1016/j.cja.2015.12.022
URL
http://www.sciencedirect.com/science/article/pii/S1000936116000066
Keywords
optimization estimation support vector machines metaheuristic astronautics aeronautics

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