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http://nopr.niscpr.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 |
| ISSN: | 0975-1025 (Online); 0971-0426 (Print) |
| Appears in Collections: | IJFTR Vol.25(1) [March 2000] |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| IJFTR 25(1) 31-36.pdf | 1.14 MB | Adobe PDF | View/Open |
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