Efficient Neural Network Modeling for Flight and Space Dynamics Simulation
This paper represents an efficient technique for neural network modeling of flight and space dynamics simulation. The technique will free the neural network designer from guessing the size and structure for the required neural network model and will help to minimize the number of neurons. For linear...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2011-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2011/247294 |
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| _version_ | 1832551809701380096 |
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| author | Ayman Hamdy Kassem |
| author_facet | Ayman Hamdy Kassem |
| author_sort | Ayman Hamdy Kassem |
| collection | DOAJ |
| description | This paper represents an efficient technique for neural network modeling of flight and space dynamics simulation. The technique will free the neural network designer from guessing the size and structure for the required neural network model and will help to minimize the number of neurons. For linear flight/space dynamics systems, the technique can find the network weights and biases directly by solving a system of linear equations without the need for training. Nonlinear flight dynamic systems can be easily modeled by training its linearized models keeping the same network structure. The training is fast, as it uses the linear system knowledge to speed up the training process. The technique is tested on different flight/space dynamic models and showed promising results. |
| format | Article |
| id | doaj-art-6749602a0bea4fb989b0d88b4a8e697f |
| institution | Kabale University |
| issn | 1687-5966 1687-5974 |
| language | English |
| publishDate | 2011-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-6749602a0bea4fb989b0d88b4a8e697f2025-02-03T06:00:32ZengWileyInternational Journal of Aerospace Engineering1687-59661687-59742011-01-01201110.1155/2011/247294247294Efficient Neural Network Modeling for Flight and Space Dynamics SimulationAyman Hamdy Kassem0Aerospace Engineering Department, Cairo University, Cairo 12613, EgyptThis paper represents an efficient technique for neural network modeling of flight and space dynamics simulation. The technique will free the neural network designer from guessing the size and structure for the required neural network model and will help to minimize the number of neurons. For linear flight/space dynamics systems, the technique can find the network weights and biases directly by solving a system of linear equations without the need for training. Nonlinear flight dynamic systems can be easily modeled by training its linearized models keeping the same network structure. The training is fast, as it uses the linear system knowledge to speed up the training process. The technique is tested on different flight/space dynamic models and showed promising results.http://dx.doi.org/10.1155/2011/247294 |
| spellingShingle | Ayman Hamdy Kassem Efficient Neural Network Modeling for Flight and Space Dynamics Simulation International Journal of Aerospace Engineering |
| title | Efficient Neural Network Modeling for Flight and Space Dynamics Simulation |
| title_full | Efficient Neural Network Modeling for Flight and Space Dynamics Simulation |
| title_fullStr | Efficient Neural Network Modeling for Flight and Space Dynamics Simulation |
| title_full_unstemmed | Efficient Neural Network Modeling for Flight and Space Dynamics Simulation |
| title_short | Efficient Neural Network Modeling for Flight and Space Dynamics Simulation |
| title_sort | efficient neural network modeling for flight and space dynamics simulation |
| url | http://dx.doi.org/10.1155/2011/247294 |
| work_keys_str_mv | AT aymanhamdykassem efficientneuralnetworkmodelingforflightandspacedynamicssimulation |