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| 003 | OSt | ||
| 005 | 20250408101111.0 | ||
| 008 | 250217s2024 |||a|||f m||| 000 0 eng d | ||
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_aEG-GICUC _beng _cEG-GICUC _dEG-GICUC _erda |
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_aeng _beng _bara |
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| 049 | _aDeposit | ||
| 082 | 0 | 4 | _a005.31 |
| 092 |
_a005.31 _221 |
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| 097 | _aM.Sc | ||
| 099 | _aCai01.13.01.M.Sc.2024.Ad.U | ||
| 100 | 0 |
_aAdham Esmat Abdelaziz Mousa, _epreparation. |
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| 245 | 1 | 0 |
_aUnknown configuration autopilot platform design using machine learning / _cby Adham Esmat Abdelaziz Mousa ; Supervision of Prof. Dr. Gamal Mahmoud El-Bayomi, Prof. Dr. Osama Saaid Mohamady. |
| 246 | 1 | 5 | _aتصميم منظومة طيار آلى للطائرات غير محددة التكوين باستخدام تعلم الآلة / |
| 264 | 0 | _c2024. | |
| 300 |
_a172 pages : _billustrations ; _c30 cm. + _eCD. |
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| 336 |
_atext _2rda content |
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| 337 |
_aUnmediated _2rdamedia |
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| 338 |
_avolume _2rdacarrier |
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| 502 | _aThesis (M.Sc)-Cairo University, 2024. | ||
| 504 | _aBibliography: pages 80 | ||
| 520 | _aOne of the ways to realize unknown configuration autopilot is the usage of system identification to estimate the aircraft parameters based on the variation of A/C configuration and flight conditions. The system identification needs an initial condition rather than using random values to find the parameters, to avoid the probability of converging to the wrong set of parameters. Our approach is the usage of machine learning to identify the initial conditions based on aircraft data. Also, the approach discussed in this thesis acts as a basis for real-time system identification where the aircraft model becomes more accurate by feeding real-time data during the flight. This thesis implements a machine learning life cycle on a dataset which is built from scratch as part of the thesis contribution | ||
| 530 | _aIssues also as CD. | ||
| 546 | _aText in English and abstract in Arabic & English. | ||
| 650 | 7 |
_aMachine Learning _2qrmak |
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| 653 | 0 |
_aUnknown Configuration Autopilot _aMachine Learning _aFlight Dynamics _aAircraft Dataset _aSystem Identification |
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| 700 | 0 |
_aGamal Mahmoud El-Bayomi _ethesis advisor. |
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| 700 | 0 |
_aOsama Saaid Mohamady _ethesis advisor. |
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| 900 |
_b01-01-2024 _cGamal Mahmoud El-Bayomi _cOsama Saaid Mohamady _dMohamed Madbouly Abdelrahman _dOmar El-Farouk Abdelhameed _UCairo University _FFaculty of Engineering _DDepartment of Aerospace Engineering |
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_aShimaa _eHuda |
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_2ddc _cTH _e21 _n0 |
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| 999 | _c170885 | ||