Crude oil prices and volatility prediction by a hybrid model based on kernel extreme learning machine

DOI10.3934/MBE.2021402zbMath1501.91170OpenAlexW3200866000MaRDI QIDQ2092197

Yazhi Zhao, Hongli Niu

Publication date: 2 November 2022

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2021402

zbMATH Keywords

volatilityhybrid modelvariational mode decompositioncrude oil predictionkernel extreme learning machine

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Interest rates, asset pricing, etc. (stochastic models) (91G30)

Cites Work

• Crude oil price prediction based on a dynamic correcting support vector regression machine
• A survey of randomized algorithms for training neural networks
• Variational Mode Decomposition
• Ensemble Forecasting for Complex Time Series Using Sparse Representation and Neural Networks

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