journal article·1995-09

Yarn Strength Prediction Using Neural Networks

Luo Cheng, David L. Adams

Textile Research Journal· Volume 65· Issue 9
Publisher page

Abstract

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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Textile materials and evaluations

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Motion Control Inc., Dallas, Texas 75220, U.S.A.

References (11)

Show source-provided references
1. Aarts, E. · 1987
2. Avitzur, Ron · Dr. Dobb's J · 1992 · 32
3. Baba, N. · 1992
4. Blum, Adam · 1992
5. 10.1177/00405175820520010610.1177/004051758205200106 ↗
6. 10.1016/0893-6080(89)90020-810.1016/0893-6080(89)90020-8 ↗
7. 10.1117/12.16432610.1117/12.164326 ↗
8. Masters, Timothy · 1993
9. 10.1177/00405175770470100810.1177/004051757704701008 ↗
10. Rumelhart, D.E. , Hinton, G., Williams , R.J., Learning Internal Representations by Error Propagation , in "Parallel Distributed Processing," vol. 1, MIT Press, Cam-bridge, MA, 1986, pp. 318-362.
11. Troudet, T.