The use of fabric surface and mechanical properties to predict fabric hand stiffness

Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/5113

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DC Field	Value	Language
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
Appears in Collections:	School of Engineering

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