The prediction model of worsted yarn quality based on CNN–GRNN neural network

被引:3
|
作者
Zhenlong Hu
Qiang Zhao
Jun Wang
机构
[1] Donghua University,College of Textiles
[2] Zhejiang Yuexiu University of Foreign Languages,College of Network Communication
来源
关键词
Worsted yarn strength index; CNN; GRNN; CNN–GRNN;
D O I
暂无
中图分类号
学科分类号
摘要
It is key indexes of worsted yarn quality such as worsted yarn strength index, etc., and it can well control worsted yarn quality by predicting yarn strength index, etc. Generally, it is generally used to predict yarn strength indexes such as multiple linear regression (MLR) algorithm, support vector machine (SVM) and backpropagation neural network (BPNN). This paper proposes a new neural network; it combines convolutional neural network (CNN) with general regression neural network (GRNN), which is written as the CNN–GRNN. It used 1900 sets of data to train CNN–GRNN, SVM and BPNN. It tested CNN–GRNN, MLR, SVM and BPNN with 10 sets of data. The CNN–GRNN neural network is the best accuracy among these four algorithms.
引用
收藏
页码:4551 / 4562
页数:11
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