Application of principal component analysis and artificial neural networks in the determination of filler dispersion during polymer extrusion processes

Application of principal component analysis and artificial neural networks in the determination of filler dispersion during polymer extrusion processes

Mineral filler-reinforced polymer is an important family of polymers designed to achieve high mechanical impact strength. The state of mineral filler dispersion in a polymer matrix strongly affects the mechanical properties of the product and is an important information for the extrusion-based fabri...

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Bibliographic Details
Main Author: Yan, Jian
Format: Others
Published: 2003
Online Access:http://spectrum.library.concordia.ca/2164/1/MQ83888.pdf
Yan, Jian <http://spectrum.library.concordia.ca/view/creators/Yan=3AJian=3A=3A.html> (2003) Application of principal component analysis and artificial neural networks in the determination of filler dispersion during polymer extrusion processes. Masters thesis, Concordia University.

Internet

http://spectrum.library.concordia.ca/2164/1/MQ83888.pdf
Yan, Jian <http://spectrum.library.concordia.ca/view/creators/Yan=3AJian=3A=3A.html> (2003) Application of principal component analysis and artificial neural networks in the determination of filler dispersion during polymer extrusion processes. Masters thesis, Concordia University.

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