Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/24619
Title: Prediction of single yarn tenacity of ring-and rotor-spun yarns from HVI results using artificial neural networks
Authors: Majumdar, Abhijit
Majumdar, Prabal Kumar
Sarkar, Bijan
Keywords: Artificial neural network;Bundle tenacity;Cotton fibre;Ring yarn;Rotor yarn;Yarn tenacity
Issue Date: Jun-2004
Publisher: NISCAIR-CSIR, India
IPC Code: Int. Cl.7 G06N 3/02; D02G 3/00
Abstract: Artificial neural network (ANN) models for predicting the single yarn tenacity of ring- and rotor- spun yarns form the cotton fibre properties, measured by high volume instrument, have been presented. Seven cotton fibre properties and yarn fineness have been used as the inputs to the neural network. Different network structures have been used to optimize the prediction performance. The relative importance of all the cotton fibre properties has also been quantified. The ANN models could predict the single yarn tenacity with less than 5% and 2% mean error in case of ring- and rotor- spun yarns respectively.Yarn fineness, fibre bundle tenacity, elongation and length uniformity are the dominant input parameters which influence the single yarn tenacity of spun yarns.
Page(s): 157-162
URI: http://hdl.handle.net/123456789/24619
ISSN: 0975-1025 (Online); 0971-0426 (Print)
Appears in Collections:IJFTR Vol.29(2) [June 2004]

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