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题名:
data prediction in manufacturing: an improved approach using least squares support vector machines
作者: Liao Zaifei ; Yang Tian ; Lu Xinjie ; Wang Hongan
会议文集: Proceedings - 2009 1st International Workshop on Database Technology and Applications, DBTA 2009
会议名称: 2009 1st International Workshop on Database Technology and Applications, DBTA 2009
会议日期: April 25,
出版日期: 2009
会议地点: Wuhan, Hubei, China
关键词: Gears ; Manufacture ; Multilayer neural networks
出版地: United States
收录类别: EI
ISBN: 9780769536040
部门归属: (1) Graduate University, Chinese Academy of Sciences, Beijing, China; (2) Institute of Software, Chinese Academy of Sciences, Beijing, China; (3) State Key Lab. of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China
主办者: Wuhan University of Science and Technology; Huazhong University of Science and Technology; Huazhong Normal University; Harbin Institute of Technology; Wuhan University; I and M/CI Joint Chapter of IEEE Ukraine Section
英文摘要: Support vector machine (SVM) is a set of related supervised learning methods used for classification and regression based on statistical learning theory. In this paper, we present a least squares support vector machines (LSSVM) regression method based on relative error for manufacturing industries to estimate the true value of imprecise measured data during production logistics process. Our method has already been successfully applied in Manufacturing Execution System (MES) of some petrochemical enterprises in China. © 2009 IEEE.
内容类型: 会议论文
URI标识: http://ir.iscas.ac.cn/handle/311060/8412
Appears in Collections:人机交互技术与智能信息处理实验室_会议论文

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Recommended Citation:
Liao Zaifei,Yang Tian,Lu Xinjie,et al. data prediction in manufacturing: an improved approach using least squares support vector machines[C]. 见:2009 1st International Workshop on Database Technology and Applications, DBTA 2009. Wuhan, Hubei, China. April 25,.
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