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:Ji, C
作者机构:[Ji, Cun; Liu, Shijun; Yang, Chenglei; Wu, Lei; Pan, Li; Meng, Xiangxu] Shandong Univ, Sch Comp Sci & Technol, Jinan 2501101, Peoples R China.; [Yan 更多
会议名称:20th IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD)
会议日期:MAY 04-06, 2016
来源:2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
出版年:2016
页码:111-116
关键词:time series data; importance data point; piecewise linear; representation; fitting error
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
收录类别:CPCI-S
WOS核心被引频次:3
资源类型:会议论文
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