Improved EEMD-based crude oil price forecasting using LSTM networks
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Jia-Qi Zhu | Qing-Biao Wu | Yu-Xi Wu | Qing-biao Wu | Yu-Xi Wu | Jia-Qi Zhu | Jia-Qi Zhu
[1] Sam Mirmirani,et al. A Comparison of VAR and Neural Networks with Genetic Algorithm in Forecasting Price of Oil , 2003, IC-AI.
[2] N. Huang,et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.
[3] Navdeep Jaitly,et al. Towards End-To-End Speech Recognition with Recurrent Neural Networks , 2014, ICML.
[4] Ling Tang,et al. LSSVR ensemble learning with uncertain parameters for crude oil price forecasting , 2017, Appl. Soft Comput..
[5] Ling Tang,et al. A hybrid grid-GA-based LSSVR learning paradigm for crude oil price forecasting , 2016, Neural Computing and Applications.
[6] F. Diebold,et al. Comparing Predictive Accuracy , 1994, Business Cycles.
[7] Jianping Li,et al. A deep learning ensemble approach for crude oil price forecasting , 2017 .
[8] Ling Tang,et al. A non-iterative decomposition-ensemble learning paradigm using RVFL network for crude oil price forecasting , 2017, Appl. Soft Comput..
[9] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[10] Lean Yu,et al. A randomized-algorithm-based decomposition-ensemble learning methodology for energy price forecasting , 2018, Energy.
[11] M. A. Kaboudan,et al. Compumetric forecasting of crude oil prices , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).
[12] Ling Tang,et al. Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach , 2015 .
[13] Ling Tang,et al. EEMD-LSSVR-Based Decomposition-and-Ensemble Methodology with Application to Nuclear Energy Consumption Forecasting , 2011, 2011 Fourth International Joint Conference on Computational Sciences and Optimization.
[14] Alex Graves,et al. DRAW: A Recurrent Neural Network For Image Generation , 2015, ICML.
[15] Xueyong Liu,et al. The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model , 2017 .
[16] C. Aloui,et al. Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling , 2012 .
[17] A. Lanza,et al. Modeling and forecasting cointegrated relationships among heavy oil and product prices , 2005 .
[18] Ekin Tokat,et al. Forecasting oil price movements with crack spread futures , 2009 .
[19] Hua Han,et al. Bandwidth Empirical Mode Decomposition and its Application , 2008, Int. J. Wavelets Multiresolution Inf. Process..
[20] Hubert Cardot,et al. A new boosting algorithm for improved time-series forecasting with recurrent neural networks , 2008, Inf. Fusion.
[21] Kin Keung Lai,et al. Hybrid approaches based on LSSVR model for container throughput forecasting: A comparative study , 2013, Appl. Soft Comput..
[22] Jiaqiu Wang,et al. Local online kernel ridge regression for forecasting of urban travel times , 2014 .
[23] Ai Jun Hou,et al. A Nonparametric GARCH Model of Crude Oil Price Return Volatility , 2012 .
[24] Ling Tang,et al. Ensemble Forecasting for Complex Time Series Using Sparse Representation and Neural Networks , 2017 .
[25] Norden E. Huang,et al. Ensemble Empirical Mode Decomposition: a Noise-Assisted Data Analysis Method , 2009, Adv. Data Sci. Adapt. Anal..
[26] Ling Tang,et al. An EEMD-based multi-scale fuzzy entropy approach for complexity analysis in clean energy markets , 2017, Appl. Soft Comput..
[27] Ling Tang,et al. A Novel CEEMD-Based EELM Ensemble Learning Paradigm for Crude Oil Price Forecasting , 2015, Int. J. Inf. Technol. Decis. Mak..
[28] He Nie,et al. Dynamic linkages among the gold market, US dollar and crude oil market , 2018 .
[29] Yudong Wang,et al. Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets , 2016 .
[30] K. Lai,et al. A new approach for crude oil price analysis based on Empirical Mode Decomposition , 2008 .
[31] Ronald Hagen,et al. How is the international price of a particular crude determined , 1994 .
[32] Zebin Yang,et al. Online big data-driven oil consumption forecasting with Google trends , 2019, International Journal of Forecasting.
[33] Lean Yu,et al. Assessing Potentiality of Support Vector Machine Method in Crude Oil Price Forecasting , 2017 .
[34] Ling Tang,et al. Forecasting Oil Price Trends with Sentiment of Online News Articles , 2017, Asia Pac. J. Oper. Res..
[35] N. Huang,et al. A new view of nonlinear water waves: the Hilbert spectrum , 1999 .
[36] K. Lai,et al. Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm , 2008 .