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Fuzzy linear regression model on mulberry silk cocoon characteristics

Niharendu Bikash Kar (Central Sericultural Research and Training Institute Berhampore, Berhampore, India)
Subhasis Das (Government College of Engineering and Textile Technology, Berhampore, India)
Anindya Ghosh (Government College of Engineering and Textile Technology, Serampore, India)
Debamalya Banerjee (Department of Production Engineering, Jadavpur University, Kolkata, India)

Research Journal of Textile and Apparel

ISSN: 1560-6074

Article publication date: 15 August 2019

Issue publication date: 21 August 2019

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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

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