| dc.contributor.author | Tuigong, David R. | |
| dc.contributor.author | Xin, Ding | |
| dc.date.accessioned | 2021-08-27T14:17:17Z | |
| dc.date.available | 2021-08-27T14:17:17Z | |
| dc.date.issued | 2005 | |
| dc.identifier.uri | https://doi.org/10.1108/RJTA-09-02-2005-B005 | |
| dc.identifier.uri | http://ir.mu.ac.ke:8080/jspui/handle/123456789/5113 | |
| dc.description.abstract | A study on predicting the stiffness of woven fabric using an artificial neural network was conducted. A neural network system trained with a back-propagation algorithm performed functional mapping between the fabric surface and mechanical properties and the evaluated hand stiffness values. The correlation coefficient was applied to confirm the effectiveness of the model that had been developed. It was established that a hand characteristic value of stiffness can be predicted from the mechanical and surface properties of fabric. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Emerald Group Publishing Limited | en_US |
| dc.subject | Back propagation | en_US |
| dc.subject | Correlation coefficient | en_US |
| dc.subject | Fabric stiffness | en_US |
| dc.subject | Neural network | en_US |
| dc.title | The use of fabric surface and mechanical properties to predict fabric hand stiffness | en_US |
| dc.type | Article | en_US |
| Files | Size | Format | View |
|---|---|---|---|
|
There are no files associated with this item. |
|||