Title :
A neural network system for designing new stretch fabrics
Author :
Alibi, Hamza ; Fayala, Faten ; Jemni, Abdelmajid ; Xianyi Zeng
Author_Institution :
Lab. of Study of the Thermal & Energy Syst. (LESTE), Univ. of Monastir, Monastir, Tunisia
Abstract :
In this paper, an artificial neural network (ANN) aided system for designing knit stretch materials based on the virtual leave one out approach is presented. This system aims at modeling the relation between functional properties (outputs) and structural parameters (inputs) of knitted fabrics made from pure yarn cotton (cellulose) and viscose (regenerated cellulose) fibers and plated knitted with elasthane (Lycra) fibers. Knitted fabric structure type, yarn count, yarn composition, gauge, elasthane fiber proportion (%), elasthane yarn linear density, fabric thickness and fabric areal density, were used as inputs to ANN model. These models have been validated by a testing data. The developed neural model allows designers to optimize the structure of knit stretch materials according to the functional properties.
Keywords :
cotton fabrics; design engineering; fabrics; neural nets; polymer fibres; production engineering computing; textile fibres; woven composites; yarn; ANN; Lycra; artificial neural network; design; elasthane fiber proportion; elasthane yarn linear density; fabric areal density; fabric thickness; gauge; knit stretch materials; plated knitted fabrics; regenerated cellulose fibers; stretch fabrics; viscose fibers; yarn composition; yarn cotton; yarn count; Artificial neural networks; Cotton; Fabrics; Neurons; Training; Yarn; Artificial neural network; Comfort-stretch; Elastic recovery; Elongation; Knit fabrics; Virtual leave one out;
Conference_Titel :
Electrical Engineering and Software Applications (ICEESA), 2013 International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4673-6302-0
DOI :
10.1109/ICEESA.2013.6578362