Identifying the key factors influencing Chinese carbon intensity using machine learning, the random forest algorithm, and evolutionary analysis

LIU Weidong, TANG Zhipeng, XIA Yan, HAN Mengyao, JIANG Wanbei

Acta Geographica Sinica ›› 2019, Vol. 74 ›› Issue (12) : 2592-2603.

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Acta Geographica Sinica ›› 2019, Vol. 74 ›› Issue (12) : 2592-2603. DOI: 10.11821/dlxb201912012
Resources, Environment and Sustainable Development

Identifying the key factors influencing Chinese carbon intensity using machine learning, the random forest algorithm, and evolutionary analysis

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{{article.zuoZheEn_L}}. {{article.title_en}}[J]. {{journal.qiKanMingCheng_EN}}, 2019, 74(12): 2592-2603 https://doi.org/10.11821/dlxb201912012

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