| 基于短相关ARIMA模型的网络流量预测 |
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| 引用本文： | 党小超,阎林.基于短相关ARIMA模型的网络流量预测[J].计算机工程,2012,38(13):71-74. |
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| 作者姓名： | 党小超 阎林 |
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| 作者单位： | 1. 西北师范大学网络教育学院,兰州,730070
2. 西北师范大学数学与信息科学学院,兰州,730070 |
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| 基金项目： | 甘肃省科技支撑计划基金资助项目 |
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| 摘 要： | 不同日期同一时刻的网络流量存在相关性和突发性。为准确预测网络流量，提出一种短相关ARIMA模型。对模型定阶后，运用改进的建模方法推导模型参数，使参数随样本数据的变化而更新。实验结果表明，与AR模型和ARIMA模型相比，该模型能更好地描述网络的相关性和自相似性，预测精度较高。
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| 关 键 词： | 用户行为 流量预测 ARIMA模型 时间序列 网络流量 短相关性 |
| 收稿时间： | 2011-08-23 |
Network Traffic Forecast Based on Short Related ARIMA Model |
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| DANG Xiao-chao
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YAN Lin.Network Traffic Forecast Based on Short Related ARIMA Model[J].Computer Engineering,2012,38(13):71-74. |
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| Authors: | DANG Xiao-chao YAN Lin |
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| Affiliation: | b(a.College of Network Education;b.College of Mathematics & Information Science,Northwest Normal University,Lanzhou 730070,China) |
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| Abstract: | There are features of relativity and sudden in the same moment of different date.In order to forecast the network traffic,this paper puts forward a related short ARIMA model.After the model sets up,the parameters is educed by using improved method.The parameters of the model can update automatically according to the changeable data.Experimental results shows that the related short ARIMA model can better describe relativity and self similarity,and makes higher forecast precision compared with AR and ARIMA model. |
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| Keywords: | user behavior traffic forecast ARIMA model time series network traffic short relativity |
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