Short-term forecasting of natural gas prices by using a novel hybrid method based on a combination of the CEEMDAN-SE-and the PSO-ALS-optimized GRU network

Citations

Cited by:

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11. Xie, Gang & Jiang, Fuxin & Zhang, Chengyuan, 2023. "A secondary decomposition-ensemble methodology for forecasting natural gas prices using multisource data," Resources Policy, Elsevier, vol. 85(PA).
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14. Yang, Jiuqiang & Lin, Niantian & Zhang, Kai & Fu, Chao & Zhang, Chong, 2024. "Transfer learning-based hybrid deep learning method for gas-bearing distribution prediction with insufficient training samples and uncertainty analysis," Energy, Elsevier, vol. 299(C).
15. Ai, Chunyu & He, Shan & Fan, Xiaochao & Wang, Weiqing, 2023. "Chaotic time series wind power prediction method based on OVMD-PE and improved multi-objective state transition algorithm," Energy, Elsevier, vol. 278(C).
16. Wang, Yue & Wang, Zhong & Luo, Yuyan, 2024. "A hybrid carbon price forecasting model combining time series clustering and data augmentation," Energy, Elsevier, vol. 308(C).
17. Ouyang, Zisheng & Lu, Min & Ouyang, Zhongzhe & Zhou, Xuewei & Wang, Ren, 2024. "A novel integrated method for improving the forecasting accuracy of crude oil: ESMD-CFastICA-BiLSTM-Attention," Energy Economics, Elsevier, vol. 138(C).
18. Bingzi Jin & Xiaojie Xu, 2025. "Machine learning price index forecasts of flat steel products," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 38(1), pages 97-117, March.
19. Feng, Zhong-kai & Huang, Qing-qing & Niu, Wen-jing & Yang, Tao & Wang, Jia-yang & Wen, Shi-ping, 2022. "Multi-step-ahead solar output time series prediction with gate recurrent unit neural network using data decomposition and cooperation search algorithm," Energy, Elsevier, vol. 261(PA).
20. Haoran Zhao & Sen Guo, 2023. "Carbon Trading Price Prediction of Three Carbon Trading Markets in China Based on a Hybrid Model Combining CEEMDAN, SE, ISSA, and MKELM," Mathematics, MDPI, vol. 11(10), pages 1-21, May.
21. László Vancsura & Tibor Tatay & Tibor Bareith, 2025. "Navigating AI-Driven Financial Forecasting: A Systematic Review of Current Status and Critical Research Gaps," Forecasting, MDPI, vol. 7(3), pages 1-49, July.
22. Oleksandr Castello & Marina Resta, 2023. "A Machine-Learning-Based Approach for Natural Gas Futures Curve Modeling," Energies, MDPI, vol. 16(12), pages 1-22, June.
23. Rabin K. Jana & Indranil Ghosh, 2025. "A residual driven ensemble machine learning approach for forecasting natural gas prices: analyses for pre-and during-COVID-19 phases," Annals of Operations Research, Springer, vol. 345(2), pages 757-778, February.
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