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计算机工程 ›› 2008, Vol. 34 ›› Issue (16): 105-106. doi: 10.3969/j.issn.1000-3428.2008.16.037

• 网络与通信 • 上一篇    下一篇

基于小波神经网络的流量混沌时间序列预测

刘 渊1,2,戴 悦1,曹建华1   

  1. (1. 江南大学信息工程学院,无锡 214122;2. 南京理工大学计算机学院,南京 210094)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-08-20 发布日期:2008-08-20

Traffic Flow Chaotic Time Series Prediction Based on Wavelet Neural Network

LIU Yuan1,2, DAI Yue1, CAO Jian-hua1   

  1. (1. College of Information Engineering, Jiangnan University, Wuxi 214122;2. School of Computer, Nanjing University of Science & Technology, Nanjing 210094)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-08-20 Published:2008-08-20

摘要: 在Takens提出的相空间重构模型基础上,应用小波变换对其进行改进,充分考虑噪声对重构结果的影响。将小波神经网络混沌时间序列预测方法引入网络流量预测中,介绍小波神经网络的基本构造和学习方法。实验表明,与RBF神经预测方法相比,小波神经网络预测方法的逼近效果更好、误差更小。

关键词: 网络流量, 相空间重构, 小波神经网络

Abstract: Based on the phase space reconstruction improved by wavelet transformation, this paper takes influence of wavelet denoising into account, and introduces the method of chiastic time series predictor based on wavelet neural network traffic flow prediction. Experimental results show that, comparing with RBF neural prediction method, wavelet neural network prediction method approaches better result, and the error margin is smaller.

Key words: network traffic flow, phase space reconstruction, wavelet neural network

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