Evaluate Fabric Wrinkle Grade Based on Subtractive Clustering Adaptive Network Fuzzy Inference Systems

Abstract:

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In this paper, a new method of subtractive clustering adaptive network fuzzy inference systems is proposed to assess degree of wrinkle in the fabric. The clustering center can be gotten through subtractive clustering algorithm, which is the base to set up adaptive network inference systems. Firstly, subtractive clustering algorithm is used to confirm the structure of fuzzy neural network, then, fuzzy inference system is used to process pattern recognition. Finally, four kinds of fabric wrinkle feature parameters are used to verify the results on real fabric. The results show the applicability of the proposed method to real data.

Info:

Periodical:

Advanced Materials Research (Volumes 332-334)

Edited by:

Xiaoming Qian and Huawu Liu

Pages:

1505-1510

DOI:

10.4028/www.scientific.net/AMR.332-334.1505

Citation:

X. B. Yang "Evaluate Fabric Wrinkle Grade Based on Subtractive Clustering Adaptive Network Fuzzy Inference Systems", Advanced Materials Research, Vols. 332-334, pp. 1505-1510, 2011

Online since:

September 2011

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Price:

$35.00

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