作者
Pelin Gurkan Unal, Mustafa Erdem Üreyen, Diren Mecit
发表日期
2012/1
期刊
Fibers and Polymers
卷号
13
页码范围
87-95
出版商
The Korean Fiber Society
简介
In our previous works, we had predicted cotton ring yarn properties from the fiber properties successfully by regression and ANN models. In this study both regression and artificial neural network has been applied for the prediction of the bursting strength and air permeability of single jersey knitted fabrics. Fiber properties measured by HVI instrument and yarn properties were selected as independent variables together with wales’ and courses’ number per square centimeter. Firstly conventional ring yarns were produced from six different types of cotton in four different yarn counts (Ne 20, Ne 25, Ne 30, and Ne 35) and three different twist multipliers (α e 3.8, α e 4.2, and α e 4.6). All the yarns were knitted by laboratory circular knitting machine. Regression and ANN models were developed to predict the fabric properties. It …
学术搜索中的文章
Predicting properties of single jersey fabrics using regression and artificial neural network models
PG Unal, ME Üreyen, D Mecit - Fibers and Polymers, 2012