Air traffic is increasing worldwide at a steady annual rate, and airport congestion is already a major issue for air traffic controllers. The traditional method of traffic flow prediction is difficult to adapt to complex air traffic conditions. Due to its self-learning, self-organizing, self-adaptive and anti-jamming capability, the neural network can predict more effectively the air traffic flow than the traditional methods can. A good method for training is an important problem in the prediction of air traffic flow with neural network. This paper will try to find a new model to solve the traffic flow prediction problem by back propagation neural network.
Research of Air Traffic Flow Forecasts Based on BP Neural Network
Advanced Materials Research ; 671-674 ; 2912-2915
2013-03-11
4 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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