A non-iterative decomposition-ensemble learning paradigm using RVFL network for crude oil price forecasting

To address time consuming and parameter sensitivity in the emerging decomposition- ensemble models, this paper develops a non-iterative learning paradigm without iterative training process. Different from the most existing decomposition-ensemble models using statistical or iterative approaches as individual forecasting tools, the proposed work otherwise employs the efficient and fast non-iterative algorithm—random vector functional link (RVFL)...