Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/24858
Title: Modelling of tensile properties of needle-punched nonwovens using artificial neural networks
Authors: Debnath, S
Madhusoothanan, M
Srinivasmoorthy, V R
Keywords: Artificial neural network;Initial modulus;Jute/polypropylene;Modelling;Needle-punched fabric;Tenacity
Issue Date: Mar-2000
Publisher: NISCAIR-CSIR, India
Abstract: The modelling of tensile properties of needle-punched nonwoven fabrics produced from the blends of jute and polypropylene fibres with varying fabric weight, needling density and blend ratio has been done. The tenacity and initial modulus values of needle-punched nonwoven fabrics have been predicted with the help of empirical model (using multiple regression analysis) and artificial neural networks and compared with the experimental values. The artificial neural network model is found to be much better and more accurate than an empirical model. An attempt has also been made for the experimental verification of the predicted values for extrapolated input variables. The prediction by artificial neural network model shows better results than that by empirical model even for the extrapolated input variables.
Page(s): 31-36
URI: http://hdl.handle.net/123456789/24858
ISSN: 0975-1025 (Online); 0971-0426 (Print)
Appears in Collections:IJFTR Vol.25(1) [March 2000]

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