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Monthly Henry Hub natural gas spot prices forecasting using variational mode decomposition and deep belief network
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- Shiqiu Zhu & Yuanying Chi & Kaiye Gao & Yahui Chen & Rui Peng, 2022. "Analysis of Influencing Factors of Thermal Coal Price," Energies, MDPI, vol. 15(15), pages 1-16, August.
- Yonghui Duan & Xiaotong Zhang & Xiang Wang & Yingying Fan & Kaige Liu, 2025. "A Novel Forecasting System with Data Preprocessing and Machine Learning for Containerized Freight Market," Mathematics, MDPI, vol. 13(10), pages 1-22, May.
- Pala, Zeydin, 2023. "Comparative study on monthly natural gas vehicle fuel consumption and industrial consumption using multi-hybrid forecast models," Energy, Elsevier, vol. 263(PC).
- Hu, Yusha & Li, Jigeng & Hong, Mengna & Ren, Jingzheng & Man, Yi, 2022. "Industrial artificial intelligence based energy management system: Integrated framework for electricity load forecasting and fault prediction," Energy, Elsevier, vol. 244(PB).
- Wei, Zhaohao & Chai, Jian & Dong, Jichang & Lu, Quanying, 2022. "Understanding the linkage-dependence structure between oil and gas markets: A new perspective," Energy, Elsevier, vol. 257(C).
- Luo, Keyu & Guo, Qiang & Li, Xiafei, 2022. "Can the return connectedness indices from grey energy to natural gas help to forecast the natural gas returns?," Energy Economics, Elsevier, vol. 109(C).
- Su, Jian & Wang, Wenya & Bai, Yang & Zhou, Peng, 2025. "Measuring the natural gas price features of the Asia-Pacific market from a complex network perspective," Energy, Elsevier, vol. 314(C).
- 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).
- Beibei Hu & Yunhe Cheng, 2023. "Prediction of Regional Carbon Price in China Based on Secondary Decomposition and Nonlinear Error Correction," Energies, MDPI, vol. 16(11), pages 1-22, May.
- Xu, Zhiwei & Wang, Xuefei & Zhang, Teng, 2024. "The international natural gas price and its cross-sectional pricing implication: Evidence from Chinese stock market," Energy, Elsevier, vol. 313(C).
- Guo, Kun & Kang, Yuxin & Ma, Dandan & Lei, Lei, 2024. "How do climate risks impact the contagion in China's energy market?," Energy Economics, Elsevier, vol. 133(C).
- Xiaojie Xu & Yun Zhang, 2023. "Steel price index forecasting through neural networks: the composite index, long products, flat products, and rolled products," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(4), pages 563-582, December.
- Luo, Keyu & Ye, Yong, 2024. "How responsive are retail electricity prices to crude oil fluctuations in the US? Time-varying and asymmetric perspectives," Research in International Business and Finance, Elsevier, vol. 69(C).
- Zhang, Jiahao & Chen, Xiaodan & Wei, Yu & Bai, Lan, 2023. "Does the connectedness among fossil energy returns matter for renewable energy stock returns? Fresh insights from the Cross-Quantilogram analysis," International Review of Financial Analysis, Elsevier, vol. 88(C).
- Yang, Wendong & Sun, Shaolong & Hao, Yan & Wang, Shouyang, 2022. "A novel machine learning-based electricity price forecasting model based on optimal model selection strategy," Energy, Elsevier, vol. 238(PC).
- Wu, Siping & Liu, Junjie & Liu, Lang, 2024. "Interval price predictions for coal using a new multi-scale ensemble model," Energy, Elsevier, vol. 313(C).
- 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.
- 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.
- Banerjee, Ameet Kumar & Sensoy, Ahmet & Goodell, John W., 2024. "Connectivity and spillover during crises: Highlighting the prominent and growing role of green energy," Energy Economics, Elsevier, vol. 129(C).
- 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.
- Yang, Weifei & Xiao, Changlai & Zhang, Zhihao & Liang, Xiujuan, 2022. "Identification of the formation temperature field of the southern Songliao Basin, China based on a deep belief network," Renewable Energy, Elsevier, vol. 182(C), pages 32-42.
- Wang, Jun & Cao, Junxing & Yuan, Shan & Cheng, Ming, 2021. "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," Energy, Elsevier, vol. 233(C).
- Wang, Xiangning & Huang, Qian & Zhang, Shuguang, 2023. "Effects of macroeconomic factors on stock prices for BRICS using the variational mode decomposition and quantile method," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
- Lahmiri, Salim, 2024. "Fossil energy market price prediction by using machine learning with optimal hyper-parameters: A comparative study," Resources Policy, Elsevier, vol. 92(C).
- Zhang, Jiahao & Zhang, Yifeng & Wei, Yu & Wang, Zhuo, 2024. "Normal and extreme impact and connectedness between fossil energy futures markets and uncertainties: Does El Niño-Southern Oscillation matter?," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 188-215.
- Qin Lu & Jingwen Liao & Kechi Chen & Yanhui Liang & Yu Lin, 2024. "Predicting Natural Gas Prices Based on a Novel Hybrid Model with Variational Mode Decomposition," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 639-678, February.