# 基于Kohonen神经网络的组合式流量预测模型Combined Prediction Model of Network Traffic Based on Kohonen Neural Network

Abstract: Considering that the original prediction model whose accuracy is low, and which highly depends on the training data and can’t well described the characteristics of network traffic, we proposed a mixed traffic prediction model. The model is based on the Kohonen neural network feartures, that is, quickly learning rate, highly classification accuracy and strongly anti-noise. By wavelet trans-forming, we decompose the network traffic into high frequency part and the low frequency part, and the high frequency part is dealt by using Kohonen neural network prediction model, the low frequency part by using autoregressive AR model to predict by using Matlab to simulat. Through the experiment we conclude this combination prediction model can improve the prediction accu-racy on multiple time scales and the nonlinear changing network traffic.

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