Citation map · Study

SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

A randomized-algorithm-based decomposition-ensemble learning methodology for energy price forecasting

10 references·13 citing·49 second hop

FromToDepth

this work references cited by second hop

References

2004Oil Price Shocks and the Macroeconomy: What Has Been Learned Since 1996494 cited
2017A deep learning ensemble approach for crude oil price forecasting383 cited
2017Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression306 cited
2005Modeling and forecasting cointegrated relationships among heavy oil and product prices172 cited
2015Comparing Variational and Empirical Mode Decomposition in Forecasting Day-Ahead Energy Prices160 cited
2017A non-iterative decomposition-ensemble learning paradigm using RVFL network for crude oil price forecasting153 cited
2014A Novel CEEMD-Based EELM Ensemble Learning Paradigm for Crude Oil Price Forecasting138 cited
2008Forecasting oil price movements with crack spread futures122 cited
2017Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis109 cited
2013Hybrid approaches based on LSSVR model for container throughput forecasting: A comparative study107 cited

Cited by

2020Crude oil price forecasting based on a novel hybrid long memory GARCH-M and wavelet analysis model63 cited
2019Energy price prediction based on independent component analysis and gated recurrent unit neural network58 cited
2023What can be learned from the historical trend of crude oil prices? An ensemble approach for crude oil price forecasting

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

52 cited

2021A novel crude oil price trend prediction method: Machine learning classification algorithm based on multi-modal data features48 cited

2019Why do EMD‐based methods improve prediction? A multiscale complexity perspective46 cited

2021Multi-Perspective Crude Oil Price Forecasting with a New Decomposition-Ensemble Framework46 cited

2020A novel BEMD-based method for forecasting tourist volume with search engine data43 cited

2023Crude oil price prediction using deep reinforcement learning38 cited

2022A novel hybrid model integrating modified ensemble empirical mode decomposition and LSTM neural network for multi-step precious metal prices prediction36 cited

2019An effective and robust decomposition-ensemble energy price forecasting paradigm with local linear prediction35 cited

2021A memory-trait-driven decomposition–reconstruction–ensemble learning paradigm for oil price forecasting35 cited

2019Forecasting stock market returns by combining sum-of-the-parts and ensemble empirical mode decomposition34 cited

2023A novel interval-based hybrid framework for crude oil price forecasting and trading33 cited