Prediction of Yarn Strength from Fiber Properties Using Fuzzy ARTMAP

Author

Raonak Zaman
Donald C. Wunsch, Missouri University of Science and TechnologyFollow

Abstract

The count-strength-product (CSP) of cotton yarn is a complex function of fiber properties and spinning performance. The traditional way of predicting yarn CSP is using linear multiple regression. The correlation coefficient between actual CSP and predicted CSP obtained from linear regression is almost always less than 0.9. In this paper, we used a Fuzzy ARTMAP network to predict yarn CSP from fiber properties and spinning performance. Fiber properties and spinning data were used as inputs to ART_a, and yarn CSP was used as ART_b input. Our objectives are: better prediction of the quality of the end product, and to determine the optimum set of fiber properties to make reliable predictions. Several experiments were designed with different combinations of fiber properties (based on the measuring instruments used in collecting those properties) as ART_a inputs. To improve relative accuracy of prediction, three voter networks were used in each experiment. During training, order of the training data was scrambled to create 3 ARTMAP networks. The ART_b templates in the voter networks indicates the range of CSP for any particular inputs to the ART_a. Since CSP is a continuous analog value, the boundary of ART_b templates is usually not fixed among the voters. To improve absolute accuracy of prediction, we took a Fuzzy OR function among the three chosen voter templates during recall to reduce the span of the range. When predicting, each ART_b template is represented by its center of gravity. In each experiment, the correlation coefficient between the actual and the predicted CSP was better than 0.95. A combination of all fiber properties from traditional and Advanced Fiber Information System (AFIS) tests made marginally better prediction than any other combination of fiber properties including when fiber properties from all the tests were fed into ART_a.

Recommended Citation

R. Zaman and D. C. Wunsch, "Prediction of Yarn Strength from Fiber Properties Using Fuzzy ARTMAP," Proceedings of the International Conference on Vision, Recognition, Action: Neural Models of Mind and Machine, Boston University, Jan 1997.

Meeting Name

International Conference on Vision, Recognition, Action: Neural Models of Mind and Machine (1997: May 28-31, Boston, MA)

Department(s)

Electrical and Computer Engineering

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 1997 Boston University, All rights reserved.

Publication Date

01 Jan 1997