Yayıncı "Korean Fiber Soc" için listeleme
Toplam kayıt 4, listelenen: 1-4
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Comparison of artificial neural network and linear regression models for prediction of ring spun yarn properties. I. Prediction of yarn tensile properties
(Korean Fiber Soc, 2008)In this study artificial neural network (ANN) models have been designed to predict the ring cotton yam properties from the fiber properties measured on HVI (high volume instrument) system and the performance of ANN models ... -
Comparison of artificial neural network and linear regression models for prediction of ring spun yarn properties. II. Prediction of yarn hairiness and unevenness
(Korean Fiber Soc, 2008)The objective of this second part of the study is to develop artificial neural network models for the prediction of yarn hairiness and unevenness and to compare the performance of ANN models with our previous statistical ... -
Predicting properties of single jersey fabrics using regression and artificial neural network models
(Korean Fiber Soc, 2012)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 ... -
Spinning Performance and Antibacterial Activity of SeaCell (R) Active/Cotton Blended Rotor Yarns
(Korean Fiber Soc, 2009)Microorganisms can lead to functional, hygienic and aesthetic (e. g. deterioration, staining) problems on textile products. Natural fibers especially cotton are more easily affected by microorganisms. Blending of cotton ...