Prediction of Rotor Spun Yarn Strength Using Adaptive Neuro-fuzzy Inference System and Linear Multiple Regression Methods

被引：1
|
作者：
狄欧
王新厚
机构：
[1] China
[2] China Key Laboratory of Science & Technology of Eco-Textile
[3] College of Textiles Donghua University
[4] Ministry of Education
[5] Shanghai 200051
[6] Shanghai 201620
来源：
Journal of Donghua University(English Edition) | 2008年 / 01期
关键词：
ANFIS; yarn strength; rotor spun yarn; properties of fiber;
D O I：
10.19884/j.1672-5220.2008.01.010
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 multiple regression model.The impact of each fiber property is also illustrated.
引用
收藏
页码：48 / 52
页数：5
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