一种改进的RBF神经网络及其在短期交通量预测中的应用

An Improved RBF Neural Network and Its Application in the Predicton of Short-term Traffic Volume

文中提出了一种改进的RBF神经网络最近邻聚类学习算法,并将其应用于短期交通量预测中。实验结果表明,改进算法的拟合效果明显优于常规最近邻聚类学习算法的拟合效果,可以明显提高RBF神经网络的性能。

An improved nearest neighbor-clustering learning algorithm for radial basis function (RBF) neural network is presented. Then the improved algorithm is applied to the prediction of short-term traffic volume. The experimental results show that the fitting effect of the improved algorithm is apparently superior to that of the conventional nearest neighbor-clustering learning algorithm and the performance of RBF neural network can be improved apparently.