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Optimal online soft sensor for product quality monitoring in propylene polymerization process

  • Published:2015-02 Issue: Volume:149 Page:1216-1224
  • ISSN:0925-2312
  • Container-title:Neurocomputing
  • language:en
  • Short-container-title:Neurocomputing

Author:

Cheng Zhong,Liu Xinggao

Funder

NSFC–CNPC

National High Technology Research and Development Program

Zhejiang Provincial Natural Science Foundation for Distinguished Young Scientists

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference32 articles.

1. Mathematical modeling, optimization, and quality control of high pressure polymerization reactors;Kiparissides;Ploym. Rev.,1993

2. A design of experiments study on the factors affecting variability in the melt index measurement;Bafna;J. Appl. Polym. Sci.,1997

3. In-process vibrational spectroscopy and ultrasound measurements in polymer melt extrusion;Coates;Polymer,2003

4. Data-driven soft sensors in the process industry;Kadlec;Comp. Chem. Eng.,2009

5. Inferential model for industrial polypropylene melt index prediction with embedded priori knowledge and delay estimation;Lou;Ind. Eng. Chem. Res.,2012
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