Fuzzy linear regression model on mulberry silk cocoon characteristics
Research Journal of Textile and Apparel
ISSN: 1560-6074
Article publication date: 15 August 2019
Issue publication date: 21 August 2019
Abstract
Purpose
This study aims to propose a fuzzy linear regression (FLR) model to deal with the vagueness or fuzziness of the underlying relationship between silk cocoon and yarn quality.
Design/methodology/approach
Shell ratio percentage, defective cocoon percentage and cocoon volume are considered as significant independent variables to predict the quality of silk cocoons. Input and output parameters of the FLR model are considered as non-fuzzy, but the underlying relationship between the variables is assumed to be fuzzy.
Findings
The fuzzy regression model shows its superiority against conventional multiple linear regression model for estimation of silk cocoon characteristics. It is inferred that the fuzziness in underlying relationship between the parameters can be handled efficiently by FLR model.
Originality/value
A rigorous experimental work has been carried out on 40 lots of mulberry silk cocoons to generate real-world data set to characterize silk cocoons’ quality in a fuzzy environment.
Keywords
Acknowledgements
The work was supported by Central Sericultural Research & Training Institute, Berhampore, West Bengal, India, and Government College of Engineering & Textile Technology Berhampore, West Bengal, India.
Citation
Kar, N.B., Das, S., Ghosh, A. and Banerjee, D. (2019), "Fuzzy linear regression model on mulberry silk cocoon characteristics", Research Journal of Textile and Apparel, Vol. 23 No. 3, pp. 201-211. https://doi.org/10.1108/RJTA-03-2019-0012
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited