Abstract
Recently, more and more attention has been drawn by the aircraft’s maneuvering problem. This problem is very significant for improving performance of the nonlinear and unsteady modeling methods used for aircrafts at high angles of attack. In this paper, support vector machine (SVM) and artificial neural network are introduced into unsteady aerodynamics modeling. The experimental results show that the generality and precision have been significantly improved using these two methods, which verifies that machine learning methods can be applied to unsteady aerodynamic modeling.
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Jiang, Y., Zhao, Q., Zhu, J. (2015). Unsteady Aerodynamics Modeling Using SVM and Artificial Neural Network. In: Deng, Z., Li, H. (eds) Proceedings of the 2015 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 336. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46469-4_62
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DOI: https://doi.org/10.1007/978-3-662-46469-4_62
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