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What is Predicting Cotton Yarn Properties with SVM about?

This paper discusses the use of support vector machine (SVM) regression to predict cotton yarn properties based on fiber characteristics, demonstrating that SVM models outperform artificial neural network (ANN) models in prediction accuracy. The study employs k-fold cross validation to assess the generalization capabilities of both models, revealing high accuracy in predicting properties such as tenacity and hairiness. The research highlights the importance of fiber parameters in determining yarn quality an

Author

Humayun Kabir

Language

EN