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Using PLS models with both controlled and uncontrolled X variables for "Waht if..." prediction
Mid Sweden University, Faculty of Science, Technology and Media, Department of Engineering, Physics and Mathematics.
2005 (English)In: The 9th Scandinavian Symposium on Chemometrics, Reykjavik, Iceland 2005-09-30, Ornsköldsvik: NPI , 2005, 6- p.Conference paper, Published paper (Other scientific)
Abstract [en]

In real-time industrial process applications, there is often a need to predict the effects of adjustments before actually effectuated. Multivariate prediction models based on historical data works fine for predictions as long as the new X data have the correlation structure preserved. This paper shows that such can anyway be used for �What if �� decision support in presence of correlated X variables, whenever it is possible to create a help model that predicts the influence of the manipulated X variables on the rest of the X variables.

Place, publisher, year, edition, pages
Ornsköldsvik: NPI , 2005. 6- p.
Keyword [en]
algorithm PLS process predictions
National Category
Control Engineering Computer Science Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:miun:diva-3464Local ID: 3544OAI: oai:DiVA.org:miun-3464DiVA: diva2:28496
Available from: 2008-09-30 Created: 2008-09-30Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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  • en-US
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Output format
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