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This paper presents a new short-term multi-step freeway traffic flow prediction model using a radial basis function neural network with fuzzy c-means clustering. The fuzzy c-mean clustering algorithm was used to determine the center position of the hidden layer of neural network. A gradient descent method was used to solve the weights from the hidden layer to the output layer. The real traffic data is used to demonstrate that the algorithm is effective for freeway traffic flow prediction.