Prediction of Rotor Spun Yarn Strength Using Adaptive Neuro-fuzzy Inference System and Linear Multiple Regression Methods |
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Authors: | NURWAHA Deogratias WANG Xin-hou |
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Affiliation: | [1]College of Textiles, Donghua University, Shanghai 201620, China; [2]Key Laboratory of Science & Technology of Eco-Textile, Ministry of Education, Donghua University, Shanghai 200051, China |
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Abstract: | This paper presents a comparison study of two models for predicting the strength of rotor spun cotton yarns from fiber properties. The adaptive neuro-fuzzy system inference (ANFIS) and Multiple Linear Regression models are used to predict the rotor spun yarn strength. Fiber properties and yarn count are used as inputs to train the two models and the count-strength-product (CSP) was the target. The predictive performances of the two models are estimated and compared. We found that the ANFIS has a better predictive power in comparison with linear multipleregression model. The impact of each fiber property is also illustrated. |
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Keywords: | ANFIS yarn strength rotor spun yarn properties of fiber |
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