Predicting the Breaking Elongation of Ring Spun Cotton Yarns Using Mathematical, Statistical, and Artificial Neural Network Models

PRABAL KUMAR MAJUMDAR; ABHIJIT MAJUMDAR

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Predicting the Breaking Elongation of Ring Spun Cotton Yarns Using Mathematical, Statistical, and Artificial Neural Network Models

机译：使用数学，统计和人工神经网络模型预测环锭纺棉纱的断裂伸长率

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This paper presents a comparative study of three modeling methodologies for predicting the breaking elongation of ring spun cotton yarns. Constituent cotton fiber properties and yarn count are used as inputs to these models. The predictive powers of the three different models—mathematical, statistical, and artificial neural network—are estimated and compared. The relative importance of various cotton fiber properties measured by a high volume instrument is also investigated using the artificial neural network model.

机译：本文对预测环锭纺棉纱断裂伸长率的三种建模方法进行了比较研究。棉纤维的成分和纱线支数用作这些模型的输入。估计并比较了三种不同模型（数学，统计和人工神经网络）的预测能力。还使用人工神经网络模型研究了通过高容量仪器测得的各种棉纤维性能的相对重要性。

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来源
《Textile Research Journal》 |2004年第7期|p.652-655|共4页
作者
PRABAL KUMAR MAJUMDAR; ABHIJIT MAJUMDAR;
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作者单位

College of Textile Technology, Serampore, West Bengal 712 201, India;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
原文格式 PDF
正文语种 eng
中图分类纺织工业、染整工业;
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Predicting the Breaking Elongation of Ring Spun Cotton Yarns Using Mathematical, Statistical, and Artificial Neural Network Models

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