Title :
Fabric Sewability Evaluation Based on KPCA Using SFC-RBFNN
Author_Institution :
Jiangyin Polytech. Coll., Jiangyin
Abstract :
In this paper, a supervised fuzzy clustering RBF neural network (SFC-RBFNN) based on kernel PCA is introduced for constructing the fabric sewability evaluation system. Our experimental results demonstrate that the proposed system could efficiently be used as an objective seam pucker evaluation system with high accuracy and is robust for various structures and mechanical properties of middle-thickness woolen fabric.
Keywords :
fabrics; fuzzy set theory; principal component analysis; production engineering computing; radial basis function networks; RBF neural network; fabric sewability evaluation; kernel PCA; objective seam pucker evaluation system; supervised fuzzy clustering; Fabrics; Fuzzy neural networks; Fuzzy systems; Kernel; Mechanical factors; Neural networks; Principal component analysis; Stress; System testing; Yarn; RBF neural network; fabric sewability; kernel PCA; supervised fuzzy clustering;
Conference_Titel :
Genetic and Evolutionary Computing, 2008. WGEC '08. Second International Conference on
Conference_Location :
Hubei
Print_ISBN :
978-0-7695-3334-6
DOI :
10.1109/WGEC.2008.52
