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

Zhipeng TANG1,2, Ziao MEI1,2, Weidong LIU1,2, and Yan XIA3、*
Author Affiliations
  • 1Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 2College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Institutes of Science and Development, CAS, Beijing 100190, China
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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

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    Paper Information

    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)

    DOI:10.1007/s11442-020-1753-4

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