An advanced warning model of airplane hard landing based on Adaboost
| Autor: | R Zhang, L Y T Cai, D J Huang, C Y Gao |
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| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Journal of Physics: Conference Series. 2472:012018 |
| ISSN: | 1742-6596 1742-6588 |
| Popis: | This paper breaks through the limitation of establishing early warning logic in the time dimension of the previous hard landing early warning model. In this research, flight altitude has been set as the scale of the corresponding early warning logic. According to the specific characteristics of the original flight parameter data set, the data preprocessing methods have been studied. The application of oversampling and frequency compression methods effectively solved the problems of different sample size and multi-frequency flight parameters in the original data set. On this basis, the method of ensemble learning is used to establish the early warning model of aircraft hard landing based on Adaboost. Further, the model is optimized to ensure the accuracy and generalization ability of the early warning model. Verified by the case study of the actual flight parameter data of Airbus A320 aircraft, the early warning model can realize high-precision prediction of hard landing events, which is of great significance for the improvement of the landing safety level of the aircraft in constructing both. |
| Databáze: | OpenAIRE |
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