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...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Inderscience Enterprises Ltd.
2010
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/4564/ http://irep.iium.edu.my/4564/4/Aerodynamic_derivatives_identification_for_ground.pdf |
| _version_ | 1848776350574313472 |
|---|---|
| author | Ramli, Nabilah Jamaluddin, Hishamuddin Mansor, Shuhaimi Faris, Waleed Fekry |
| author_facet | Ramli, Nabilah Jamaluddin, Hishamuddin Mansor, Shuhaimi Faris, Waleed Fekry |
| author_sort | Ramli, Nabilah |
| building | IIUM Repository |
| collection | Online Access |
| description | 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 using neural network with and without the input optimisation by PCA. Both studies are compared with the identification results from a conventional method, and it is shown that the neural network can approximate functions based on principal components extracted as well as a full-size neural network can. |
| first_indexed | 2025-11-14T14:28:42Z |
| format | Article |
| id | iium-4564 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T14:28:42Z |
| publishDate | 2010 |
| publisher | Inderscience Enterprises Ltd. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-45642011-11-22T08:51:23Z http://irep.iium.edu.my/4564/ Aerodynamic derivatives identification for ground vehicles in crosswind using neural network and PCA Ramli, Nabilah Jamaluddin, Hishamuddin Mansor, Shuhaimi Faris, Waleed Fekry TJ170 Mechanics applied to machinery. Dynamics 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 using neural network with and without the input optimisation by PCA. Both studies are compared with the identification results from a conventional method, and it is shown that the neural network can approximate functions based on principal components extracted as well as a full-size neural network can. Inderscience Enterprises Ltd. 2010 Article PeerReviewed application/pdf en http://irep.iium.edu.my/4564/4/Aerodynamic_derivatives_identification_for_ground.pdf Ramli, Nabilah and Jamaluddin, Hishamuddin and Mansor, Shuhaimi and Faris, Waleed Fekry (2010) Aerodynamic derivatives identification for ground vehicles in crosswind using neural network and PCA. International Journal of Vehicle Systems Modelling and Testing, 5 (1). pp. 59-71. ISSN 1745-6444 (O), 1745-6436 (P) http://www.inderscience.com/search/index.php?action=record&rec_id=33731 10.1504/IJVSMT.2010.033731 |
| spellingShingle | TJ170 Mechanics applied to machinery. Dynamics Ramli, Nabilah Jamaluddin, Hishamuddin Mansor, Shuhaimi Faris, Waleed Fekry Aerodynamic derivatives identification for ground vehicles in crosswind using neural network and PCA |
| title | Aerodynamic derivatives identification for ground vehicles in crosswind using neural network and PCA |
| title_full | Aerodynamic derivatives identification for ground vehicles in crosswind using neural network and PCA |
| title_fullStr | Aerodynamic derivatives identification for ground vehicles in crosswind using neural network and PCA |
| title_full_unstemmed | Aerodynamic derivatives identification for ground vehicles in crosswind using neural network and PCA |
| title_short | Aerodynamic derivatives identification for ground vehicles in crosswind using neural network and PCA |
| title_sort | aerodynamic derivatives identification for ground vehicles in crosswind using neural network and pca |
| topic | TJ170 Mechanics applied to machinery. Dynamics |
| url | http://irep.iium.edu.my/4564/ http://irep.iium.edu.my/4564/ http://irep.iium.edu.my/4564/ http://irep.iium.edu.my/4564/4/Aerodynamic_derivatives_identification_for_ground.pdf |