Forecasting Natural Gas Consumption of China Using a Novel Grey Model
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Abstract
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DOI: 10.1155/2020/3257328
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Cited by:
- Erum Rehman & Muhammad Ikram & Shazia Rehman & Ma Tie Feng, 2021. "Growing green? Sectoral-based prediction of GHG emission in Pakistan: a novel NDGM and doubling time model approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 12169-12191, August.
- Xiong, Xin & Hu, Xi & Tian, Tian & Guo, Huan & Liao, Han, 2022. "A novel Optimized initial condition and Seasonal division based Grey Seasonal Variation Index model for hydropower generation," Applied Energy, Elsevier, vol. 328(C).
- Wang, Qi & Suo, Ruixia & Han, Qiutong, 2024. "A study on natural gas consumption forecasting in China using the LMDI-PSO-LSTM model: Factor decomposition and scenario analysis," Energy, Elsevier, vol. 292(C).
- Li, Fengyun & Li, Xingmei & Zheng, Haofeng & Yang, Fei & Dang, Ruinan, 2021. "How alternative energy competition shocks natural gas development in China: A novel time series analysis approach," Resources Policy, Elsevier, vol. 74(C).
- Tiwari, Aviral Kumar & Sharma, Gagan Deep & Rao, Amar & Hossain, Mohammad Razib & Dev, Dhairya, 2024. "Unraveling the crystal ball: Machine learning models for crude oil and natural gas volatility forecasting," Energy Economics, Elsevier, vol. 134(C).
- Xiong, Xin & Hu, Xi & Guo, Huan, 2021. "A hybrid optimized grey seasonal variation index model improved by whale optimization algorithm for forecasting the residential electricity consumption," Energy, Elsevier, vol. 234(C).
- Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
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