linear time trend

基本解释

Based on PLR (piecewise linear representation) of time series, a new representation method of time-series based on trend turning point is proposed.
在时间序列分段线性表示基础上，提出一种新的基于趋势转折点的时间序列模式表示方法。
Finally built a two linear forecasting models based on smoothing of time queue about analysis of sale trend, and verified the design analysis of this paper partly.
最后，建立了基于时间序列的二次指数平滑线性预测模型，进行商品销售趋势的分析，部分验证了本文的设计分析。
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.
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。