This work investigates the application of artificial neural network modeling (ANN) to model the relationships between fiber, yarn, and fabric properties and the pilling propensity of single jersey and rib pure wool knitted fabrics based on the ICI Pilling Box method. Validation of the model on an independent validation data set suggests that the accurate prediction of pilling propensity is possible with the best performing model achieving a correlation with the subjectively rated pilling grades of approximately 85%. Importantly, it is also illustrated that a larger training set can lead to a marked improvement in the accuracy of predictions. <br /
WOS: 000366405200012This study, it was aimed to determine the equations and models for estimating th...
2nd International Conference on Agents and Artificial Intelligence, ICAART 2010 -- 22 January 2010 t...
The abrasion resistance of chenille yarn is crucially important in particular because the effect sou...
This work investigates the application of artificial neural network modeling (ANN) to model the rela...
Fabric pilling is affected by many interacting factors. This study uses artificial neural networks t...
This thesis tackles an important quality issue in the wool industry - the pilling of wool knitwear. ...
This study ranks the contribution of various fibre, yarn and fabric attributes to the pilling of woo...
WOS: 000368643200007Artificial neural network (ANN) is a mathematical model inspired by biological n...
Artificial neural network (ANN) is a mathematical model inspired by biological neural networks and i...
This thesis examined the application of data mining techniques to the issue of predicting pilling pr...
The propensity of wool knitwear to form entangled fiber balls, known as pills, on the surface is aff...
83-88Effects of fibre, yarn and fabric parameters on the pilling performance of weft knitted fabri...
In our previous works, we had predicted cotton ring yarn properties from the fiber properties succes...
Abstract: In this study, the effects of yarn parameters, on the bursting strength of the plain knitt...
This study, it was aimed to determine the equations and models for estimating the pilling propensity...
WOS: 000366405200012This study, it was aimed to determine the equations and models for estimating th...
2nd International Conference on Agents and Artificial Intelligence, ICAART 2010 -- 22 January 2010 t...
The abrasion resistance of chenille yarn is crucially important in particular because the effect sou...
This work investigates the application of artificial neural network modeling (ANN) to model the rela...
Fabric pilling is affected by many interacting factors. This study uses artificial neural networks t...
This thesis tackles an important quality issue in the wool industry - the pilling of wool knitwear. ...
This study ranks the contribution of various fibre, yarn and fabric attributes to the pilling of woo...
WOS: 000368643200007Artificial neural network (ANN) is a mathematical model inspired by biological n...
Artificial neural network (ANN) is a mathematical model inspired by biological neural networks and i...
This thesis examined the application of data mining techniques to the issue of predicting pilling pr...
The propensity of wool knitwear to form entangled fiber balls, known as pills, on the surface is aff...
83-88Effects of fibre, yarn and fabric parameters on the pilling performance of weft knitted fabri...
In our previous works, we had predicted cotton ring yarn properties from the fiber properties succes...
Abstract: In this study, the effects of yarn parameters, on the bursting strength of the plain knitt...
This study, it was aimed to determine the equations and models for estimating the pilling propensity...
WOS: 000366405200012This study, it was aimed to determine the equations and models for estimating th...
2nd International Conference on Agents and Artificial Intelligence, ICAART 2010 -- 22 January 2010 t...
The abrasion resistance of chenille yarn is crucially important in particular because the effect sou...