A neural network system for designing new stretch fabrics

Hamza Alibi, F. Fayala, A. Jemni, Xianyi Zeng
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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.
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基于神经网络的新型弹力织物设计
提出了一种基于虚拟留一方法的人工神经网络辅助针织弹力材料设计系统。该系统旨在模拟纯棉(纤维素)和粘胶(再生纤维素)纤维针织物和弹性烷(莱卡)纤维镀面针织物的功能特性(输出)和结构参数(输入)之间的关系。以针织物的结构类型、支数、纱线成分、规格、弹性体纤维比例(%)、弹性体线密度、织物厚度和织物面密度作为人工神经网络模型的输入。通过试验数据验证了模型的正确性。所开发的神经模型使设计人员能够根据织物的功能特性对织物的结构进行优化。
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