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  • 标题:Application of Partial Least-squares Regression to Material Consumption Prediction
  • 本地全文:下载
  • 作者:Si Li ; Shenyang Liu ; Xinzhong Li
  • 期刊名称:Journal of Software Engineering
  • 印刷版ISSN:1819-4311
  • 电子版ISSN:2152-0941
  • 出版年度:2016
  • 卷号:10
  • 期号:4
  • 页码:424-430
  • DOI:10.3923/jse.2016.424.430
  • 出版社:Academic Journals Inc., USA
  • 摘要:Background: Nearly all the segments about material include acquisition, storage, supplying and management have close connections with the maintenance material consumption information. The material consumption rule has a great significance on all the segments about material include acquisition, storage, supplying, management and improve the scientificalness of material support. Materials and Methods: Through making an analysis of the character of material consumption and some factors that affects material consumption, this study applies partial least-squares regression to solve the problem of material consumption prediction when the sample is small. Results: The example indicates that partial least-squares regression is much more accurate than multiple linear regressions. Conclusion: The models provide a theoretical basis for calculating reserves of material scientifically and have the vital important guiding significance.
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