Optimal selection of heterogeneous ensemble strategies of time series forecasting with multi-objective programming

作者：

Highlights：

• A heterogeneous ensemble forecasting model of nonlinear time series is proposed.

• Both forecasting error and model divergence are considered.

• Dynamic heterogeneous mutation operator is introduced to improve MOPSO.

• The proposed model has excellent prediction performance and robustness.

摘要

•A heterogeneous ensemble forecasting model of nonlinear time series is proposed.•Both forecasting error and model divergence are considered.•Dynamic heterogeneous mutation operator is introduced to improve MOPSO.•The proposed model has excellent prediction performance and robustness.

论文关键词：Multi-objective optimization,Ensemble forecasting,Machine learning,Evolutionary algorithm,Baltic Dry Index

论文评审过程：Received 5 June 2020, Revised 14 September 2020, Accepted 2 October 2020, Available online 9 October 2020, Version of Record 15 October 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.114091