Input data selection for daily traffic flow forecasting through contextual mining and intra-day pattern recognition

作者：

Highlights：

• Select appropriate historical days of data to enhance forecasting performance.

• Utilize contextual information to measure the similarities between data and target.

• Match target day with the clustered group with ordered contextual factors.

摘要

•Select appropriate historical days of data to enhance forecasting performance.•Utilize contextual information to measure the similarities between data and target.•Match target day with the clustered group with ordered contextual factors.

论文关键词：Traffic flow forecasting,Input data selection,Clustering,Pattern recognition,NSGA-II

论文评审过程：Received 6 January 2020, Revised 30 January 2021, Accepted 7 March 2021, Available online 18 March 2021, Version of Record 3 April 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114902