Collision avoidance using neural networks learned by genetic algorithms
Durand, Nicolas ; Alliot, Jean-Marc ; Noailles, Joseph
HAL, hal-00937688 / Harvested from HAL
Text on HAL
As Air Traffic keeps increasing, many research programs focus on collision avoidance techniques. In this paper, a neural netwok learned by genetic algorithm is introduced to solve conflicts between two aircrafts. The learned NN is then tested on different conflicts and compared to the optimal solution. Results are very promising.
Publié le : 1996-06-01
Classification:  Air Traffic Control,  collision avoidance,  neural networks,  genetic algorithms,  [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC] 
@article{hal-00937688,
     author = {Durand, Nicolas and Alliot, Jean-Marc and Noailles, Joseph},
     title = {Collision avoidance using neural networks learned by genetic algorithms},
     journal = {HAL},
     volume = {1996},
     number = {0},
     year = {1996},
     language = {en},
     url = {http://dml.mathdoc.fr/item/hal-00937688}
}

Durand, Nicolas; Alliot, Jean-Marc; Noailles, Joseph. Collision avoidance using neural networks learned by genetic algorithms. HAL, Tome 1996 (1996) no. 0, . http://gdmltest.u-ga.fr/item/hal-00937688/