Forecasting Crude Oil Prices Using Ensemble Empirical Mode Decomposition and Sparse Bayesian Learning

Forecasting Crude Oil Prices Using Ensemble Empirical Mode Decomposition and Sparse Bayesian Learning

Crude oil is one of the most important types of energy and its prices have a great impact on the global economy. Therefore, forecasting crude oil prices accurately is an essential task for investors, governments, enterprises and even researchers. However, due to the extreme nonlinearity and nonstati...

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Bibliographic Details
Main Authors:	Taiyong Li, Zhenda Hu, Yanchi Jia, Jiang Wu, Yingrui Zhou
Format:	Article
Language:	English
Published:	MDPI AG 2018-07-01
Series:	Energies
Subjects:	crude oil prices time series forecasting ensemble empirical mode decomposition (EEMD) sparse Bayesian learning (SBL) energy forecasting
Online Access:	http://www.mdpi.com/1996-1073/11/7/1882

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