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A network traffic prediction model based on recurrent wavelet neural network

机译:基于递归小波神经网络的网络流量预测模型

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摘要

The network traffic prediction model is the foundation of network performance analysis and designing. The traditional traffic models have the weakness of low-level efficiency. The recurrent wavelet neural network(RWNN) based on E Iman network was proposed in the paper, and the dynamic gradient descent algorithm of RWNN was given, and could be used in the network traffic prediction. Experimental results show that the network traffic prediction model based on RWNN is feasible and effective.
机译:网络流量预测模型是网络性能分析和设计的基础。传统的流量模型具有低效率的缺点。提出了一种基于E Iman网络的递归小波神经网络(RWNN),并给出了RWNN的动态梯度下降算法,可用于网络流量预测。实验结果表明,基于RWNN的网络流量预测模型是可行和有效的。

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