A Hybrid Modeling using Clustering Algorithm for Teztile Slashing Process

摘要：

The slashing is a very important procedure in textile manufacturing process which can improve warp quality, loom efficiency and reduce warp break. A hybrid modeling method is proposed for textile slashing process. Data are divided to multiple subsets by clustering algorithm, and then artificial neural networks (ANN) and partial least square (PLS) regression are used to model multiple sub-models respectively according to size of subset. The weight coefficient of sub-model is obtained by Lagrange multiplier method, and the whole model is established by combining multiple sub-models. The simulation result shows that the proposed hybrid modeling method has a better predictive accuracy and robustness.

关键词： Data Modeling Slashing Process Clustering Artificial Neural Networks Partial Least Squares

作者: Zhang Yuxian Liu Min Wang Jianhui Wang Dan Ma Yunfei

作者单位: Department of Automation, Tsinghua University, Beijing 100084, China Faculty of Information Science and Engineering, Northeastern University, Shenyang 110004, China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 5751-5754

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）