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A novel method based on numerical fitting for oil price trend forecasting

  • Published:2018-06 Issue: Volume:220 Page:154-163
  • ISSN:0306-2619
  • Container-title:Applied Energy
  • language:en
  • Short-container-title:Applied Energy

Author:

Zhao Lu-Tao,Wang Yi,Guo Shi-Qiu,Zeng Guan-Rong

Funder

National Natural Science Foundation of China

China Scholarship Council

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Cited by 43 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Modeling the Dynamics of Oil Price Fluctuations Using the System Dynamics Approach;2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM);2023-12-18

2. Crude oil price forecasting with machine learning and Google search data: An accuracy comparison of single-model versus multiple-model;Engineering Applications of Artificial Intelligence;2023-08

3. What can be learned from the historical trend of crude oil prices? An ensemble approach for crude oil price forecasting;Energy Economics;2023-07

4. Seasonal learning based ARIMA algorithm for prediction of Brent oil Price trends;Multimedia Tools and Applications;2023-02-28

5. GRU and LSTM Based Adaptive Prediction Model of Crude Oil Prices: Post-Covid-19 and Russian Ukraine War;Proceedings of the 2023 6th International Conference on Computers in Management and Business;2023-01-13
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