Predicting Yarn Unevenness Using RBF Neural Network

被引：0

作者：

Li Huijun ^{[1
]}

Wang Xinhou ^{[1
]}

机构：

[1] Donghua Univ, Coll Text, Shanghai 201620, Peoples R China

来源：

PROCEEDINGS OF THE 12TH INTERNATIONAL WOOL RESEARCH CONFERENCE, VOLS I AND II | 2010年

关键词：

RBF; CV value; knots; NEPS;

D O I：

暂无

中图分类号：

TB3 [工程材料学]; TS1 [纺织工业、染整工业];

学科分类号：

0805 ; 080502 ; 0821 ;

摘要：

The objective of this research is to predict yarn unevenness. The model of predicting yam unevenness is built based on standard RBF neural network. The RBF neural networks are trained with HVI test results of cotton and USTER TENSOJET 5-S400 test results of yarn. The results show prediction models based on RBF neural network are very precise and efficient.

引用

页码：971 / 973

页数：3

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