linear time trend

基本解釋

Based on PLR (piecewise linear representation) of time series, a new representation method of time-series based on trend turning point is proposed.
在時間序列分段線性表示基礎(chǔ)上，提出一種新的基于趨勢轉(zhuǎn)折點的時間序列模式表示方法。
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，建立了基于時間序列的二次指數(shù)平滑線性預(yù)測模型，進行商品銷售趨勢的分析，部分驗證了本文的設(shè)計分析。
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.
文章考慮網(wǎng)絡(luò)流量非線性的特點，通過不同的數(shù)學(xué)模型將流量時間序列分解成趨勢成分、周期成分、突變成分和隨機成分。