| 基于支持向量机的纺纱质量预测模型研究 |
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| 引用本文： | 吕志军,杨建国,项前,王晓玲.基于支持向量机的纺纱质量预测模型研究[J].控制与决策,2007,22(6):693-696. |
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| 作者姓名： | 吕志军 杨建国 项前 王晓玲 |
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| 作者单位： | 东华大学,机械工程学院,上海,201620 |
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| 基金项目： | 国家自然科学基金项目（70371040）;国家经贸委技术创新项目（02LJ-14-05-01）. |
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| 摘 要： | 纱线的生产是一个多环节的复杂工业过程．其质量控制大多需要依赖领域专家的个人经验,为此提出一种基于支持向量机的纱线质量预测模型．探讨了模型选择与验证问题,并利用“网格搜索”法对模型参数进行了优化,试验结果表明,在小样本和“噪音”数据环境下．支持向量机模型仍能保持一定的预测精度,与人工神经网络模型相比,更适应于真实纺纱生产过程．
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| 关 键 词： | 支持向量机 统计学习 预测模型 人工神经网络 纺纱生产 |
| 文章编号： | 1001-0920（2007）06-0693-04 |
| 收稿时间： | 2006/2/19 0:00:00 |
| 修稿时间： | 2006-02-192006-04-01 |
Research on support vector machines based predictive model for yarn quality |
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| LV Zhi-jun,YANG Jian-guo,XIANG Qian,WANG Xiao-ling.Research on support vector machines based predictive model for yarn quality[J].Control and Decision,2007,22(6):693-696. |
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| Authors: | LV Zhi-jun YANG Jian-guo XIANG Qian WANG Xiao-ling |
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| Affiliation: | College of Mechanical Engineering, Donghua University, Shanghai 201620, China. |
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| Abstract: | Yarn production is a multiple stage complex industrail process,and its quality control is heavly depended upon the domain expert's experience.An SVM model for predicting yarn properties is presented,and the model parameters are optimized with "grid-research" method.Experimental results show that under the real data sets and small population circumstances,SVM models are capable of maintaining the stability of predictive accuracy,and more suitable for noisy spinning process. |
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| Keywords: | Support vector machines Statistical learning Predictive model Artificial neural networks Spinning process |
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