Crude oil price prediction: A comparison between AdaBoost-LSTM and AdaBoost-GRU for improving forecasting performance

Author:

Busari Ganiyu Adewale,Lim Dong Hoon

Publisher

Elsevier BV

Subject

Computer Science Applications,General Chemical Engineering

Reference34 articles.

1. Machine learning approach for crude oil price prediction with Artificial Neural Networks-Quantitative (ANN-Q) model;Abdullah;Int'l Joint Con NN,2010

2. An empirical comparison of machine learning models for time series forecasting;Ahmed;Econom. Rev.,2010

3. Daily crude oil price forecasting model using arima, generalized autoregressive conditional heteroscedastic and support vector machines;Ahmed;Am. J. Appl. Sci.,2014

4. Comparative analysis of recurrent neural network architectures for reservoir inflow forecasting;Apaydin;Water (Basel),2020

5. Forecasting the nominal brent oil price with VARs—One model fits all?;Beckers;IMF,2015

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