@inproceedings{8791b287b691420eaaddb92a3fa21f99,
title = "Solving the steady flight state of aircraft based on hybrid genetic algorithm",
abstract = "Steady flat flight is widely used in the flight simulator training as an ideal initial state. To ensure the accurate solving of the steady flat flight state a hybrid genetic algorithm is put forward. The algorithm based on the new concept of {"}individual learning potentiality{"} make the Lamarckian learning and Baldwinina learning genetic algorithm combination together organically according to the particularity of the solving in the steady flat flight state. The algorithm could make the advantage of the learning into full play and make the disadvantage into inhibitory. The algorithm has generality which just use the state variable to calculate and can be independent of the airplane dynamic. Simulation result shows that the new algorithm combined the tow learning mechanism has made a good effect.",
keywords = "Baldwinina learning, Genetic algorithm, Individual learning potentiality, Lamarckian learning, Steady flight state",
author = "Luan Zhibo and Huang Qitao and Jiang Hongzhou and Li Hongren",
year = "2009",
doi = "10.1109/ICIC.2009.159",
language = "英语",
isbn = "9780769536347",
series = "2009 2nd International Conference on Information and Computing Science, ICIC 2009",
pages = "200--203",
booktitle = "2009 2nd International Conference on Information and Computing Science, ICIC 2009",
note = "2009 2nd International Conference on Information and Computing Science, ICIC 2009 ; Conference date: 21-05-2009 Through 22-05-2009",
}