Investigation on Stiffness of Finished ...
Document type :
Article dans une revue scientifique: Article original
Permalink :
Title :
Investigation on Stiffness of Finished Stretch Plain Knitted Fabrics Using Fuzzy Decision Trees and Artificial Neural Networks
Author(s) :
Baghdadi, R. [Auteur]
Alibi, H. [Auteur]
Fayala, F. [Auteur]
Zeng, Xianyi [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Alibi, H. [Auteur]
Fayala, F. [Auteur]
Zeng, Xianyi [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Journal title :
Fibers and Polymers
Abbreviated title :
Fiber. Polym.
Volume number :
-
Pages :
-
Publication date :
2021-02-17
ISSN :
1229-9197
English keyword(s) :
Fuzzy decision trees
ANN
Virtual-leave-one-out
Stretch finished knitted fabrics
Stiffness
ANN
Virtual-leave-one-out
Stretch finished knitted fabrics
Stiffness
HAL domain(s) :
Sciences de l'ingénieur [physics]
English abstract : [en]
Stiffness is one of the most important utility properties of textile materials and plays a significant role in well-being due to its influence on physiological comfort [1]. On that point are a great deal of structural ...
Show more >Stiffness is one of the most important utility properties of textile materials and plays a significant role in well-being due to its influence on physiological comfort [1]. On that point are a great deal of structural properties of textile materials also operating parameters (knitting+finishing) influencing stiffness and there are also statistically significant interactions between the principal factors determining the stiffness of textile materials. As part of our research, we proposed to facilitate the industry adjust the most relevant operating parameters before actual manufacturing to reach the desired stiffness and satisfy consumers. It warrants the application of artificial neural nets (ANNs) to predict the stiffness of finished knitted fabrics and the utilization of the Fuzzy Decision Tree in the selection procedure, to puzzle out the problem of insufficient data and boil down the complexity of predictive models. Moreover, a virtual leave one out approach dealing with overfitting phenomenon and allowing the selection of the optimal neural network architecture was applied.Show less >
Show more >Stiffness is one of the most important utility properties of textile materials and plays a significant role in well-being due to its influence on physiological comfort [1]. On that point are a great deal of structural properties of textile materials also operating parameters (knitting+finishing) influencing stiffness and there are also statistically significant interactions between the principal factors determining the stiffness of textile materials. As part of our research, we proposed to facilitate the industry adjust the most relevant operating parameters before actual manufacturing to reach the desired stiffness and satisfy consumers. It warrants the application of artificial neural nets (ANNs) to predict the stiffness of finished knitted fabrics and the utilization of the Fuzzy Decision Tree in the selection procedure, to puzzle out the problem of insufficient data and boil down the complexity of predictive models. Moreover, a virtual leave one out approach dealing with overfitting phenomenon and allowing the selection of the optimal neural network architecture was applied.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
ENSAIT
Junia HEI
ENSAIT
Junia HEI
Collections :
Submission date :
2023-06-20T11:41:08Z
2024-03-25T12:08:25Z
2024-03-25T12:08:25Z