Particle swarm optimization for time series motif discovery
作者：
Highlights：
• We consider the task of finding repeated segments or motifs in time series.
• We propose a new standpoint to the task: formulating it as an optimization problem.
• We apply particle swarm optimization to solve the problem.
• The proposed solution finds comparable motifs in substantially less time.
• The proposed standpoint brings in an unprecedented degree of flexibility to the task.
摘要
•We consider the task of finding repeated segments or motifs in time series.•We propose a new standpoint to the task: formulating it as an optimization problem.•We apply particle swarm optimization to solve the problem.•The proposed solution finds comparable motifs in substantially less time.•The proposed standpoint brings in an unprecedented degree of flexibility to the task.
论文关键词：Motifs,Time series,Anytime algorithms,Particle swarm optimization,Multimodal optimization
论文评审过程：Received 8 July 2015, Revised 15 October 2015, Accepted 15 October 2015, Available online 26 October 2015, Version of Record 11 December 2015.
论文官网地址：https://doi.org/10.1016/j.knosys.2015.10.021
