摘要
通过对用户行为分析,发现IP数据流具有平稳性、自相关性等特点,提出基于映射矩阵流量预测模型,并与线性模型AR、ARIMA和非线性基于反馈神经网络BP模型、Elman神经网络作对比,试验结果证明,映射矩阵模型,比现有模型具有预测精度高、收敛快等特点。
By analyzing user behavior, this paper finds that the IP data stream has smooth and self-correlation characteristics, pro- poses a prediction model based on the mapping matrix flow in comparison with the linear AR, RIMA models and nonlinear BP model based on feedback neural network, Elman neural network. The test results demonstrate that the mapping matrix model has high prediction accuracy and fast convergence characteristics compared with existing models.
出处
《计算机工程与应用》
CSCD
2013年第8期100-104,共5页
Computer Engineering and Applications
基金
西北师范大学青年教师科研能力提升计划项目(No.SYQNYB10040)
关键词
映射矩阵
预测模型
网络流量
用户行为
mapping matrix
prediction model
network traffic
user behavior