Aerodynamic derivatives identification for ground vehicles in crosswind using neural network and PCA

Aerodynamic derivatives identification for ground vehicles in crosswind using neural network and PCA

Principal component analysis (PCA) is employed in this study to reduce the size of the neural network input node. Neural network is used to identify the ground vehicle aerodynamic derivatives based on a recorded simple harmonic motion of a ground vehicle model. The study involves the identification...

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Bibliographic Details
Main Authors: Ramli, Nabilah, Jamaluddin, Hishamuddin, Mansor, Shuhaimi B., Faris, Waleed Fekry
Format: Article
Language:English
Published: Inderscience Enterprises Ltd. 2010
Subjects:
TJ Mechanical engineering and machinery
TJ181 Mechanical movements
TJ210.2 Mechanical devices and figures. Automata. Ingenious mechanism. Robots (General)
Online Access:http://irep.iium.edu.my/49833/
http://irep.iium.edu.my/49833/
http://irep.iium.edu.my/49833/
http://irep.iium.edu.my/49833/1/Aerodynamic_derivatives_identification_for_ground_vehicles_in_crosswind_using_neural_network_and_PCA.pdf

Internet

http://irep.iium.edu.my/49833/
http://irep.iium.edu.my/49833/
http://irep.iium.edu.my/49833/
http://irep.iium.edu.my/49833/1/Aerodynamic_derivatives_identification_for_ground_vehicles_in_crosswind_using_neural_network_and_PCA.pdf

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