DocumentCode
475681
Title
SFCNN Based Approach to Fabric Angle Bending Rigidity Prediction
Author
Pan, Yonghui
Author_Institution
Jiangyin Polytech. Coll., Jiangsu
Volume
1
fYear
2008
fDate
3-4 Aug. 2008
Firstpage
664
Lastpage
668
Abstract
In this paper, a supervised fuzzy clustering neural network (SFCNN) is introduced for constructing the fabric angle bending property prediction system. Our experimental results demonstrate that the proposed system could efficiently be used as a fabric angle bending rigidity prediction system with high accuracy and is robust for various structures and mechanical properties of cotton and wool fabric.
Keywords
bending; cotton fabrics; fuzzy neural nets; pattern clustering; shear modulus; textile industry; wool; cotton fabric; fabric angle bending rigidity prediction; mechanical property; supervised fuzzy clustering neural network; wool fabric; Accuracy; Automatic testing; Clothing; Communication system control; Computer networks; Cotton; Fabrics; Materials testing; Strips; Wool; Angle bending rgidity; Fabric; Supervised FCNN; Supervised fuzzy clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing, Communication, Control, and Management, 2008. CCCM '08. ISECS International Colloquium on
Conference_Location
Guangzhou
Print_ISBN
978-0-7695-3290-5
Type
conf
DOI
10.1109/CCCM.2008.278
Filename
4609596
Link To Document