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

  • Zhenlong Hu
  • Qiang Zhao
  • Jun Wang
S.I. : Emergence in Human-like Intelligence towards Cyber-Physical Systems
  • 36 Downloads

Abstract

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.

Keywords

Worsted yarn strength index CNN GRNN CNN–GRNN 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.College of TextilesDonghua UniversityShanghaiChina
  2. 2.College of Network CommunicationZhejiang Yuexiu University of Foreign LanguagesShaoxingChina

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