| Data Mining for Quality Prediction in Textile Engineering |
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| 作者姓名： | 杨建国 李蓓智 赵亚梅 |
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| 作者单位： | College of mechanical Engineering , Donghua University 200051 |
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| 基金项目： | This project is supported by China National Technology Innovation Plan |
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| 摘 要： | A data mining method for quality prediction using association rule （DMAR） is presented in this paper. Association rule is used to mine the valuable relations of items among amounts of textile process data for ANN prediction model. DMAR consists of three main steps： setup knowledge data set; data cleaning and converting; find the item set with large supports and generate the expected rules. DMAR effectively improves the precision of prediction in yarn breaking. It rapidly gets rid of the negative influence of training parameters on prediction model. Then more satisfactory quality prediction result can be reached.
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| 关 键 词： | 采矿数据 关联算法 ANN 纱纺织 |
| 收稿时间： | 2005-12-21 |
Data Mining for Quality Prediction in Textile Engineering |
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| YANG Jian-guo,LI Bei-zhi,ZHAO Ya-mei.Data Mining for Quality Prediction in Textile Engineering[J].Journal of Donghua University,2006,23(2):88-91. |
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| Authors: | YANG Jian-guo LI Bei-zhi ZHAO Ya-mei |
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| Abstract: | A data mining method for quality prediction using association rule (DMAR) is presented in this paper. Association rule is used to mine the valuable relations of items among amounts of textile process data for ANN prediction model. DMAR consists of three main steps: setup knowledge data set; data cleaning and converting; find the item set with large supports and generate the expected rules. DMAR effectively improves the precision of prediction in yarn breaking. It rapidly gets rid of the negative influence of training parameters on prediction model. Then more satisfactory quality prediction result can be reached. |
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| Keywords: | Data mining Association algorithm ANN Yarn breaking rate |
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