Multi-objective optimization of raw silk parameters using a combined support vector regression-genetic algorithm-desirability function approach-Reference-Cited by-同舟云学术

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Multi-objective optimization of raw silk parameters using a combined support vector regression-genetic algorithm-desirability function approach

Published:2023-04-25 Issue: Volume: Page:1-9
ISSN:0040-5000
Container-title:The Journal of The Textile Institute
language:en
Short-container-title:The Journal of The Textile Institute

Author:

Das Subhasis¹^ORCID,Ghosh Anindya¹^ORCID

Affiliation:

1. Government College of Engineering & Textile Technology, Berhampore, Berhampore, India

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Polymers and Plastics,General Agricultural and Biological Sciences,Materials Science (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/00405000.2023.2201066

Reference25 articles.

1. Performance of neural networks for predicting yarn properties using principal component analysis

2. Yarn Strength Prediction Using Neural Networks

3. Case-Based Reasoning System for Predicting Yarn Tenacity

4. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

5. Yarn engineering using hybrid artificial neural network-genetic algorithm model

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