标题:A piecewise linear representation method based on importance data points for time series data
作者:Ji, Cun ;Liu, Shijun ;Yang, Chenglei ;Wu, Lei ;Pan, Li ;Meng, Xiangxu
通讯作者:Liu, Shijun
作者机构:[Ji, Cun ;Liu, Shijun ;Yang, Chenglei ;Wu, Lei ;Pan, Li ;Meng, Xiangxu ] School of Computer Science and Technology, Shandong University, Jinan; 250101 更多
会议名称:20th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016
会议日期:4 May 2016 through 6 May 2016
来源:Proceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016
出版年:2016
页码:111-116
DOI:10.1109/CSCWD.2016.7565973
关键词:fitting error; importance data point; piecewise linear representation; time series data
摘要:With the development of intelligent manufacturing technology, it can be foreseen that time series data generated by smart devices will raise to an unprecedented level. For time series with high amount, high dimension and renewal speed characteristics, resulting in difficult data mining and presentation on the original time series data. This paper presented a piecewise linear representation based on importance data points for time series data, which called PLR-IDP for short. The method finds importance data points by calculating the fitting error of single point and piecewise, and then represents time series approximately by linear composed of the importance data points. Results from theoretical analysis and experiments show that PLR-IDP reduces the dimensionality, holds the main characteristic with small fitting error of segments and single points. © 2016 IEEE.
收录类别:EI;SCOPUS
Scopus被引频次:4
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84991632824&doi=10.1109%2fCSCWD.2016.7565973&partnerID=40&md5=a80205a5f2d57155a8cfb3f66d963f44
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