首页|Applying Artificial Neural Network Model on Investigating the Fiber Diameter of Polybutylene Terephthalate (PBT) Spunbonding Nonwovens: Comparison with Mathematical Statistical Method
Applying Artificial Neural Network Model on Investigating the Fiber Diameter of Polybutylene Terephthalate (PBT) Spunbonding Nonwovens: Comparison with Mathematical Statistical Method
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NETL
NSTL
Trans Tech Publications Ltd
In this paper, two models are founded and introduced to predict the fiber diameter of polybutylene terephthalate spunbonding nonwovens from the spunbonding process parameters. The results indicate the artificial neural network model has good approximation capability and fast convergence rate, and it can provide quantitative predictions of fiber diameter and yield more accurate and stable predictions than the mathematical statistical method. This area of research has great potential in the field of computer assisted design in spunbonding technology.
spunbonding nonwovenpolybutylene terephthalatefiber diametermathematical statistical methodartificial neural network model
B. Zhao
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College of Textiles, Zhongyuan University of Technology, Henan, Zhengzhou, 450007, China
NETL
NSTL
Trans Tech Publications Ltd
