为了提高流量预测准确性,将支持向量机回归应用于网络流量预测。介绍了支持向量机回归建模的关键因素,并将该模型应用于实际网络流量预测计算,同时与BP神经网络模型进行比较。结果表明,支持向量机回归模型具有更好的抗噪能力、泛化推广能力以及更高的预测精度,能够很好地预测网络流量。 In order to improve the accuracy of traffic prediction, support vector machine regression is applied to network traffic prediction. The key factors of SVM regression modeling are introduced. The model is applied to the actual network traffic prediction calculation and compared with the BP neural network model. The results show that support vector machine regression model has better anti-noise ability, generalized promotion ability and higher prediction accuracy, which can predict the network traffic well.