Hierarchical time series forecasting via Support Vector Regression in the European Travel Retail Industry

作者：

Highlights：

• A novel strategy hierarchical time series forecasting is proposed.

• Support Vector Regression is adapted for dealing with hierarchical time series.

• The proposal is successfully applied in a case study in sales forecasting.

• Best predictive performance is achieved in experiments on benchmark datasets.

摘要

•A novel strategy hierarchical time series forecasting is proposed.•Support Vector Regression is adapted for dealing with hierarchical time series.•The proposal is successfully applied in a case study in sales forecasting.•Best predictive performance is achieved in experiments on benchmark datasets.

论文关键词：Hierarchical time series,Support Vector Regression,Time series analysis,Sales forecasting

论文评审过程：Received 3 September 2018, Revised 5 May 2019, Accepted 26 June 2019, Available online 27 June 2019, Version of Record 4 July 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.06.060