A method of city traffic flow prediction based on a grey neural network

2015 ◽  
Author(s):  
X. W. Han ◽  
Y. Zhao ◽  
B. Y. Xin ◽  
D. Wang
Keyword(s):  
Neural Network ◽  
Traffic Flow ◽  
Traffic Flow Prediction ◽  
Flow Prediction

Using Hybrid Fuzzy Neural Network to Improve the Accuracy of Air Traffic Flow Forecasts

2013 ◽  
Vol 333-335 ◽  
pp. 1422-1425
Author(s):  
Ming Qiang Chen
Keyword(s):  
Neural Network ◽  
Traffic Flow ◽  
Fuzzy Neural Network ◽  
Good Method ◽  
Air Traffic ◽  
Traffic Flow Prediction ◽  
Air Traffic Controllers ◽  
Flow Prediction ◽  
Air Traffic Flow ◽  
Fuzzy Neural

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 hybrid fuzzy 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 hybrid fuzzy neural network.

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