Abstract:

In order to improve the prediction accuracy of radial basis function (RBF) neural network model for shortterm traffic flow, we propose a prediction model for shortterm traffic flow of optimized RBF neural networks based on the modified artificial bee colony (ABC) algorithm. The modified ABC algorithm is used to confirm center value and unit numbers of the hidden layers of the RBF neural networks. Then the modified RBF neural network prediction model is trained, and the efficiency of the proposed prediction model is tested through simulations on the shortterm traffic flow data of a city in four days. Experimental results of the proposed model are compared with the traditional RBF neural network model, the BP neural network model and the wavelet neural network model, which  verify the higher prediction accuracy of the proposed method.

Key words: traffic flow prediction;RBF neural network;BP neural network;wavelet neural network;artificial bee colony algorithm