Determination of temporal information granules to improve forecasting in fuzzy time series

作者：

Highlights：

• Partitioning the universe of discourse in consideration of temporal information.

• Determining intervals by time series segmentation and information granules.

• Using the proposed method forecasting accuracies were significantly improved.

• These intervals carry well-defined semantics.

• The proposed method is very robust and stable to forecast in fuzzy time series.

摘要

•Partitioning the universe of discourse in consideration of temporal information.•Determining intervals by time series segmentation and information granules.•Using the proposed method forecasting accuracies were significantly improved.•These intervals carry well-defined semantics.•The proposed method is very robust and stable to forecast in fuzzy time series.

论文关键词：Fuzzy time series,Gath–Geva (GG) clustering,Information granules,Enrollment,Segmentation

论文评审过程：Available online 31 October 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.10.046