polynomial regression

基本解釋

The sixth part forecasts the future logistics demand of Shandong Province on the basis of one linear regression, polynomial regression, gray system G(1,1) model and combination forecast model.
第六部分采用一元線性回歸、多項(xiàng)式回歸、灰色系統(tǒng)G（1，1）模型和組合預(yù)測(cè)模型對(duì)山東省現(xiàn)代物流業(yè)未來(lái)需求狀況進(jìn)行了中期預(yù)測(cè)。
The multi-element orthogonal polynomial regression is used for traditional optimization technique of parametric optimum design, and the experimental research is done by some experiential formula.
傳統(tǒng)的研究方法是采用多元正交多項(xiàng)式回歸參數(shù)優(yōu)化設(shè)計(jì)，通過(guò)獲得一些經(jīng)驗(yàn)公式來(lái)進(jìn)行實(shí)驗(yàn)研究。
The polynomial regression based on the constant-pressure filtration rate equation has been presented to handle the experimental data and compared with the methods in literature through an example.
本文從恒壓過(guò)濾速率方程出發(fā)，利用多項(xiàng)式回歸的方法求取過(guò)濾常數(shù)，并以一實(shí)例將之與教材中介紹的方法進(jìn)行了比較。