On using the modularity of recurrence network communities to detect change-point behaviour

作者：

Highlights：

• A new network algorithm to detect when time series changes concepts.

• Recurrence network communities as a proxy for quadrant scan tipping point detection.

• Real-world industrial application to streaming data and run-to-failure experiments.

摘要

•A new network algorithm to detect when time series changes concepts.•Recurrence network communities as a proxy for quadrant scan tipping point detection.•Real-world industrial application to streaming data and run-to-failure experiments.

论文关键词：Recurrence plots,Concept drift,Tipping point detection,Complex networks,Modularity

论文评审过程：Received 5 August 2020, Revised 15 December 2020, Accepted 1 March 2021, Available online 11 March 2021, Version of Record 31 March 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114837