DocumentCode :
131756
Title :
The Research on Detection Method of Cotton Contamination Based on Improved RBF Neutral Network
Author :
Huang Jing ; Jiang Ming ; Chen Hanwei
Author_Institution :
Coll. of Inf., Zhejiang Univ. of Sci. & Technol., Hangzhou, China
fYear :
2014
fDate :
10-11 Jan. 2014
Firstpage :
753
Lastpage :
756
Abstract :
For the low automation level and accuracy in detection of cotton contaminations, this paper adopts GMDH clustering algorithm to define the number of hidden nodes and the center of primary function in RBF neutral network adaptively. The improved RBF neutral network is applied to detect the cotton contaminations. The result shows that the RBF neutral network based on GMDH clustering algorithm could locate contaminations in cotton precisely, and has high location accuracy. That has significance in improving the quality of fabrics and reducing production costs.
Keywords :
contamination; cost reduction; cotton; cotton fabrics; pattern clustering; product quality; production engineering computing; radial basis function networks; textile industry; GMDH clustering algorithm; RBF neutral network; automation level; contamination location accuracy; cotton contamination detection method; fabrics quality; production cost reduction; Automation; Mechatronics; RBF neural network; basis functions centers; deformation prediction; objective clustering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2014 Sixth International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-1-4799-3434-8
Type :
conf
DOI :
10.1109/ICMTMA.2014.185
Filename :
6802803
Link To Document :
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