Time series clustering based on complex network with synchronous matching states

作者：

Highlights：

• The constructed state sequence can describe the time series more effectively.

• Time series similarity measure method is powerful and time complexity is low.

• The proposed method is suitable for clustering multiple time series data.

• It does not require to manually set the number of communities.

摘要

•The constructed state sequence can describe the time series more effectively.•Time series similarity measure method is powerful and time complexity is low.•The proposed method is suitable for clustering multiple time series data.•It does not require to manually set the number of communities.

论文关键词：Time series clustering,Complex network,Synchronous matching,Data mining

论文评审过程：Received 14 December 2021, Revised 5 July 2022, Accepted 12 August 2022, Available online 18 August 2022, Version of Record 27 August 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118543