Yarn Strength Prediction Using Neural Networks: Part I: Fiber Properties and Yarn Strength Relationship

Over the past several years, numerous relationships between fiber properties and yarn performance have been developed. The classical method for predicting yam performance is statistical analysis such as linear multiple regression. Neural networks are now a subject of interest in many fields and a to...

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Bibliographic Details
Published in:Textile research journal 1995-09, Vol.65 (9), p.495-500
Main Authors: Luo Cheng, Adams, David L.
Format: Article
Language:English
Subjects:
Fibers
Neural networks
Regression
Strength
Textiles
Trains
Yarns
Citations: Items that this one cites
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Summary:Over the past several years, numerous relationships between fiber properties and yarn performance have been developed. The classical method for predicting yam performance is statistical analysis such as linear multiple regression. Neural networks are now a subject of interest in many fields and a tool for many areas of problem solving. This study investigates the application of neural networks to yarn strength prediction. HVI test results of the 1989 crop are used to train the neural nets and performance is discussed.
ISSN:0040-5175
1746-7748
DOI:10.1177/004051759506500901