Geometric properties of partial least squares for process monitoring
نویسندگان
چکیده
Projection to latent structures or partial least squares (PLS) produces output-supervised decomposition on inputX, while principal component analysis (PCA) produces unsupervised decomposition of inputX. In this paper, the effect of outputYon theX-space decomposition in PLS is analyzed andgeometric properties of the PLS structure are revealed. Several PLS algorithms are compared in a geometric way for the purpose of process monitoring. A numerical example and a case study are given to illustrate the analysis results. © 2009 Elsevier Ltd. All rights reserved.
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ورودعنوان ژورنال:
- Automatica
دوره 46 شماره
صفحات -
تاریخ انتشار 2010