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