Journal :   International Journal of Technology

Volume No. :   4

Issue No. :  1

Year :  2014

Pages :   109-111

ISSN Print :  2231-3907

ISSN Online :  2231-3915


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Yarn Strength Prediction using Hybrid Genetic Algorithm - Fuzzy Approach



Address:   Subhasis Das, Anindya Ghosh
Government College of Engineering and Textile Technology, Berhampore, India-742 101
*Corresponding Author
DOI No:

ABSTRACT:
Yarn strength modelling and prediction has remained as the cynosure of research for the textile engineers although the investigation in this domain was first reported around one century ago [1,2]. In recent years fuzzy logic has evolved as a very popular prediction technique in textile industry. In the domain of textile technology there are plentiful examples of imprecise variables. For an example, a spinner often uses the terms like ‘fine’ and ‘coarse’ to assess the fibre and yarn count, although these terms do not constitute a well defined boundary. Although fuzzy logic is a powerful tool for dealing with imprecision and uncertainty, however, it has its inherent limitation. This limitation may be minimized by combining it with genetic algorithm (GA) which is a potential tool for global optimization. In this work an effort has been made to improve the prediction performance of fuzzy modelling of cotton yarn strength by developing a hybrid genetic algorithm- fuzzy logic model. This paper deals with modelling of GA- fuzzy model for more accurate prediction of ring spun cotton yarn strength.
KEYWORDS:
Yarn Strength Prediction using Hybrid Genetic Algorithm - Fuzzy Approach
Cite:
Subhasis Das, Anindya Ghosh. Yarn Strength Prediction using Hybrid Genetic Algorithm - Fuzzy Approach. Int. J. Tech. 4(1): Jan.-June. 2014; Page 109-111
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