基于组合优化理论的无线网络流量建模与预测

发布时间：2018-03-18 11:34

  本文选题：无线网络　切入点：自回归积分滑动平均模型　出处：《现代电子技术》2016年23期 　论文类型：期刊论文

【摘要】：无线网络流量受到上网成本、上网行为等因素的综合作用,具有随机性和周期性变化的特点,针对单一模型不能全面描述该变化特点的难题,提出基于组合优化理论的无线网络流量预测模型。首先采用自回归积分滑动平均模型进行建模,找出无线网络流量的周期性变化规律,然后采用相关向量机进行建模,找出无线网络流量的随机性变化特点,最后将它们的预测结果组合在一起进行单步和多步的无线网络流量预测实验。实验结果表明,该模型可以同时对随机性和周期性变化特点进行描述,预测精度高于单一自回归积分滑动平均模型或者相关向量机。
[Abstract]:Wireless network traffic is affected by the cost and behavior of the Internet, and has the characteristics of randomness and periodicity. In view of the problem that a single model can not fully describe the characteristics of the change, the wireless network traffic has the characteristics of randomness and periodicity. This paper presents a wireless network traffic prediction model based on combinatorial optimization theory. Firstly, the autoregressive integral moving average model is used to model the periodic variation of wireless network traffic, and then the correlation vector machine is used to model the model. The randomness characteristics of wireless network traffic are found out. Finally, the prediction results are combined to carry out single-step and multi-step wireless network traffic prediction experiments. The experimental results show that, The prediction accuracy of the model is higher than that of single autoregressive integral moving average model or correlation vector machine.
【作者单位】： 海南师范大学信息科学技术学院;海南广播电视大学琼海远程教育学院;海南师范大学信息网络与数据中心;
【分类号】：TN92
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本文编号：1629456