quality evaluation based on multivariate statistical methods

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ID: 246636
2013
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Abstract
Quality prediction models are constructed based on multivariate statistical methods, including ordinary least squares regression (OLSR), principal component regression (PCR), partial least squares regression (PLSR), and modified partial least squares regression (MPLSR). The prediction model constructed by MPLSR achieves superior results, compared with the other three methods from both aspects of fitting efficiency and prediction ability. Based on it, further research is dedicated to selecting key variables to directly predict the product quality with satisfactory performance. The prediction models presented are more efficient than tradition ones and can be useful to support human experts in the evaluation and classification of the product quality. The effectiveness of the quality prediction models is finally illustrated and verified based on the practical data set of the red wine.
Reference Key
yin2013mathematicalquality Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Shen Yin;Xiangping Zhu;Hamid Reza Karimi
Journal journal of power sources
Year 2013
DOI
10.1155/2013/639652
URL
http://dx.doi.org/10.1155/2013/639652
Keywords
civil engineering (general)mathematics engineering (general)

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