纺织学报 ›› 2008, Vol. 29 ›› Issue (4): 43-46.

• 纺织工程 • 上一篇    下一篇

基于支持向量机的纱线质量预测

项前1;杨建国1;程隆棣2   

  1. 1.东华大学机械工程学院 上海201620;2.东华大学教育部纺织面料技术重点实验室 上海201620
  • 收稿日期:2007-03-08 修回日期:2007-12-04 出版日期:2008-04-15 发布日期:2008-04-15

Yarn quality prediction by support vector machine method

XIANG Qian;YANG Jianguo;CHENG Longdi   

  1. 1.College of Mechanical Engineering;Donghua University;Shanghai 201620;China;2.Key Laboratory of Textile Science & Technology;Ministry of Education;Donghua University;Shanghai 201620;China
  • Received:2007-03-08 Revised:2007-12-04 Online:2008-04-15 Published:2008-04-15

摘要: 针对现有的优化纺纱工艺过程质量预测模型尚无法满足实际生产需要的问题,提出了纱线质量预测的支持向量机方法,并利用网格搜索对该模型的参数进行优化。经毛纱工艺实践表明,在小样本和"噪声"数据环境下,支持向量机模型仍能保持一定的预测精度,同人工神经网络模型相比,更适用于真实纺纱生产过程中的工艺控制。

Abstract: Aiming at the fact that the current yarn quality prediction model for optimizing the spinning process could not meet the needs of practical production,support vector machine(SVM) method for yarn quality prediction was proposed.This study optimized the model parameters with″grid-research″method.Experimental results of wool yarn indicate that SVM model is able to simulate spinning process to a reasonably good accuracy,and more suitable for real spinning process than ANN model.

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