文章考虑网络流量非线性的特点，通过不同的数学模型将流量时间序列分解成趋势成分、周期成分、突变成分和随机成分。
According to the character of non linear network traffic, the traffic time series is decomposed into trend component, period component, mutation component and random component.
基于时间序列分解法建立大坝变形预测模型。
The forecast model of dam deformation is set up on the basis of the time alignment decomposition method.
应用确定型的时间序列分解法乘法模型与随机型的arma模型相结合，建立重庆市主城区人口死亡率的时间序列模型。
Combined with certain type time series recount multiplicity model and random type ARMA model, establish the time series model of the death rate in Chongqing urban area.
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