Studying on the Fiber Diameter of Polypropylene (PP) Spunbonding Fabric by Means of Artificial Neural Network Model and Physical Model

Abstract:

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In this work, the artificial neural network model and physical model are established and utilized for predicting the fiber diameter of polypropylene(PP) spunbonding nonwovens from the process parameters. The artificial neural network model has good approximation capability and fast convergence rate, is used in this research. The results show the artificial neural network model can provide quantitative predictions of fiber diameter and yield more accurate and stable predictions than the physical model, which reveals that the artificial neural network model is based on the inherent principles, and it can yield reasonably good prediction results and provide insight into the relationship between process parameters and fiber diameter.

Info:

Periodical:

Key Engineering Materials (Volumes 426-427)

Edited by:

Dunwen Zuo, Hun Guo, Guoxing Tang, Weidong Jin, Chunjie Liu and Chun Su

Pages:

356-360

DOI:

10.4028/www.scientific.net/KEM.426-427.356

Citation:

B. Zhao "Studying on the Fiber Diameter of Polypropylene (PP) Spunbonding Fabric by Means of Artificial Neural Network Model and Physical Model", Key Engineering Materials, Vols. 426-427, pp. 356-360, 2010

Online since:

January 2010

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Price:

$35.00

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