rarely used spare parts

According to this, the thesis does some research on support vector machines(SVMs)based forecasting method for rarely used spare parts demand.
基于此,本文研究了基于支持向量機(jī)的不常用備件需求預(yù)測(cè)方法。

計(jì)算機(jī)科學(xué)技術(shù)

To address this problem above, the thesis makes efforts on application of multiple support vector machines (SVM) to forecast rarely used spare parts demand via designing an integrated forecasting support system.
本文引入基于有限樣本統(tǒng)計(jì)學(xué)習(xí)理論的支持向量機(jī)回歸方法,預(yù)測(cè)不常用備件需求。