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A neural network system for designing new stretch fabrics

机译:用于设计新型弹力织物的神经网络系统

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摘要

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.
机译:本文提出了一种基于虚拟留一法的人工神经网络(ANN)辅助设计针织弹力材料的系统。该系统旨在模拟由纯纱线棉(纤维素)和粘胶纤维(再生纤维素)纤维制成的针织织物的功能特性(输出)与结构参数(输入)之间的关系,并用弹性纤维(莱卡纤维)进行平板编织。针织物的结构类型,纱线支数,纱线组成,规格,弹性纤维比例(%),弹性纱线线密度,织物厚度和织物面密度被用作ANN模型的输入。这些模型已通过测试数据验证。开发的神经模型使设计人员可以根据功能特性优化针织弹力材料的结构。

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