data prediction in manufacturing: an improved approach using least squares support vector machines

	data prediction in manufacturing: an improved approach using least squares support vector machines
	Liao Zaifei; Yang Tian; Lu Xinjie; Wang Hongan
	2009
会议名称	2009 1st International Workshop on Database Technology and Applications, DBTA 2009
会议录名称	Proceedings - 2009 1st International Workshop on Database Technology and Applications, DBTA 2009
会议日期	April 25,
会议地点	Wuhan, Hubei, China
收录类别	EI
出版地	United States
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
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.
关键词	Gears Manufacture Multilayer Neural Networks
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
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/8412
专题	人机交互技术与智能信息处理实验室
推荐引用方式 GB/T 7714	Liao Zaifei,Yang Tian,Lu Xinjie,et al. data prediction in manufacturing: an improved approach using least squares support vector machines[C]. United States,2009.