Journal of Geographical Sciences, Volume. 30, Issue 5, 743(2020)
Identification of the key factors affecting Chinese carbon intensity and their historical trends using random forest algorithm
Fig. 1. Average reductions in Gini coefficient and the corresponding cumulative percentage importance as a function of carbon intensity index number
Fig. 2. Percentages of factors affecting Chinese carbon intensity in different categories between 1980 and 2017
Categorization of factors influencing carbon intensity in China
Carbon intensity indicator numbers and corresponding average reductions in Gini coefficient
Carbon intensity indicator numbers and corresponding average reductions in Gini coefficient
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Numbers of key factors affecting Chinese carbon intensity per category by year between 1980 and 2017 1(1Note: Based on length limitations,
Numbers of key factors affecting Chinese carbon intensity per category by year between 1980 and 2017 1(1Note: Based on length limitations,
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Zhipeng TANG, Ziao MEI, Weidong LIU, Yan XIA. Identification of the key factors affecting Chinese carbon intensity and their historical trends using random forest algorithm[J]. Journal of Geographical Sciences, 2020, 30(5): 743
Category: Research Articles
Received: Dec. 22, 2019
Accepted: Feb. 20, 2020
Published Online: Sep. 30, 2020
The Author Email: XIA Yan (xiayan@casipm.ac.cn)