Application of Artificial Neural Networks to Predict the Air Permeability of Woven Fabrics

被引:0
|
作者
Matusiak, Malgorzata [1 ]
机构
[1] Lodz Univ Technol, Inst Text Architecture, Ul Zeromskiego 116, PL-90924 Lodz, Poland
关键词
woven fabrics; air permeability; artificial neural networks; modelling; SPINNING PROCESS; MODEL; COTTON; INDEX;
D O I
暂无
中图分类号
TB3 [工程材料学]; TS1 [纺织工业、染整工业];
学科分类号
0805 ; 080502 ; 0821 ;
摘要
Air permeability is one of the most important utility properties of textile materials as it influences airflow through textile material. Air permeability plays a significant role in textiles for clothing due to their influence on physiological comfort. Air permeability is also very important in technical textiles, especially for filtration, automotive airbags, parachutes, etc. The air permeability of textile materials depends on their porosity. There are a lot of structural properties of textile materials influencing air permeability and there are also statistically significant interactions between the main factors influencing the air permeability of fabrics. It justifies the application of artificial neural networks (ANNs) to predict the air permeability of textile materials on the basis of their structural parameters. Within the framework of the work presented ANNs were applied to predict the air permeability of cotton woven fabrics.
引用
收藏
页码:41 / 48
页数:8
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