ABSTRACT
The prediction of traffic flow is very key importance for the traffic plan, traffic management, traffic control and safety. Recently, the experts present all kinds of prediction models. The artificial neural network is a supervised training technique, which has good paralleling process ability. RBF neural network is a kind of feed-forward neural network, which is composed of the different layers includes the input layer, hidden layer and output layer. The artificial life is the important research method for the traditional biology and the ecology, and artificial life does not emulate the life form of carbohydrate. The research of artificial life contributes to indicate the most essential feature that life needs and basic regulation of life evolution. The hybrid method of artificial life and RBF neural network is presented to predict the traffic flow. The experimental data are used to testify the traffic flow prediction ability of the hybrid method of artificial life and RBF neural network. It can be seen that the traffic flow prediction results of the hybrid method of artificial life and RBF neural network are better than those of RBF neural network and BP neural network.
