Exploring Primary Aluminum Consumption: New Perspectives from Hybrid CEEMDAN-S-Curve Model
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- Zhang, Xun & Lai, K.K. & Wang, Shou-Yang, 2008. "A new approach for crude oil price analysis based on Empirical Mode Decomposition," Energy Economics, Elsevier, vol. 30(3), pages 905-918, May.
- Ewees, Ahmed A. & Elaziz, Mohamed Abd & Alameer, Zakaria & Ye, Haiwang & Jianhua, Zhang, 2020. "Improving multilayer perceptron neural network using chaotic grasshopper optimization algorithm to forecast iron ore price volatility," Resources Policy, Elsevier, vol. 65(C).
- Jia, Hongxiang & Li, Tianjiao & Wang, Anjian & Liu, Guwang & Guo, Xiaoqian, 2021. "Decoupling analysis of economic growth and mineral resources consumption in China from 1992 to 2017: A comparison between tonnage and exergy perspective," Resources Policy, Elsevier, vol. 74(C).
- Du, J.D. & Han, W.J. & Peng, Y.H. & Gu, C.C., 2010. "Potential for reducing GHG emissions and energy consumption from implementing the aluminum intensive vehicle fleet in China," Energy, Elsevier, vol. 35(12), pages 4671-4678.
- Trevor Zink & Roland Geyer & Richard Startz, 2018. "Toward Estimating Displaced Primary Production from Recycling: A Case Study of U.S. Aluminum," Journal of Industrial Ecology, Yale University, vol. 22(2), pages 314-326, April.
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Keywords
primary aluminum; consumption mechanism; CEEMDAN; S-curve; hybrid model; volatility;All these keywords.
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