Forecasting Energy CO 2 Emissions Using a Quantum Harmony Search Algorithm-Based DMSFE Combination Model
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- Zhicong Zhang & Hao Xie & Jubing Zhang & Xinye Wang & Jiayu Wei & Xibin Quan, 2022. "Prediction and Trend Analysis of Regional Industrial Carbon Emission in China: A Study of Nanjing City," IJERPH, MDPI, vol. 19(12), pages 1-23, June.
- Wu, Lifeng & Liu, Sifeng & Liu, Dinglin & Fang, Zhigeng & Xu, Haiyan, 2015. "Modelling and forecasting CO2 emissions in the BRICS (Brazil, Russia, India, China, and South Africa) countries using a novel multi-variable grey model," Energy, Elsevier, vol. 79(C), pages 489-495.
- Yousuf, I. & Ghumman, A.R. & Hashmi, H.N. & Kamal, M.A., 2014. "Carbon emissions from power sector in Pakistan and opportunities to mitigate those," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 71-77.
- Weiye Lu & Xiaoxuan Chen & Zhuorui Song & Yuesheng Li & Jidong Lu, 2023. "A Fast Screening Method of Key Parameters from Coal for Carbon Emission Enterprises," Energies, MDPI, vol. 16(22), pages 1-14, November.
- Menglu Li & Wei Wang & Gejirifu De & Xionghua Ji & Zhongfu Tan, 2018. "Forecasting Carbon Emissions Related to Energy Consumption in Beijing-Tianjin-Hebei Region Based on Grey Prediction Theory and Extreme Learning Machine Optimized by Support Vector Machine Algorithm," Energies, MDPI, vol. 11(9), pages 1-15, September.
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Keywords
fossil fuel energy; CO 2 emissions; quantum harmony search algorithm; discounting factor; combination forecasting method;All these keywords.
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