Random vector functional link neural network based ensemble deep learning for short-term load forecasting

作者：

Highlights：

• An ensemble deep randomized network for forecasting is proposed.

• Empirical wavelet transformation is used to augment unsupervised features.

• A layer-wise tuning algorithm is proposed to optimize the structures.

• Two error metrics and statistical tests are utilized to compare the models.

摘要

•An ensemble deep randomized network for forecasting is proposed.•Empirical wavelet transformation is used to augment unsupervised features.•A layer-wise tuning algorithm is proposed to optimize the structures.•Two error metrics and statistical tests are utilized to compare the models.

论文关键词：Forecasting,Random vector functional link network,Deep learning,Machine learning

论文评审过程：Received 9 February 2022, Revised 14 May 2022, Accepted 4 June 2022, Available online 11 June 2022, Version of Record 18 June 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117784