A data-driven framework for spatiotemporal characteristics, complexity dynamics, and environmental risk evaluation of river water quality.

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第一作者： Chenning,Deng

第一单位： College of Water Sciences, Beijing Normal University, Beijing 100875, China; Chinese Research Academy of Environmental Sciences, Beijing 100012, China.

作者： Chenning,Deng ^[1] ; Lusan,Liu ^[2] ; Haisheng,Li ^[3] ; Dingzhi,Peng ^[4] ; Yifan,Wu ^[5] ; Huijuan,Xia ^[2] ; Zeqian,Zhang ^[1] ; Qiuheng,Zhu ^[1]

作者单位： College of Water Sciences, Beijing Normal University, Beijing 100875, China; Chinese Research Academy of Environmental Sciences, Beijing 100012, China. ^[1] Chinese Research Academy of Environmental Sciences, Beijing 100012, China. ^[2] Chinese Research Academy of Environmental Sciences, Beijing 100012, China. Electronic address: lihs@craes.org.cn. ^[3] College of Water Sciences, Beijing Normal University, Beijing 100875, China. Electronic address: dzpeng@bnu.edu.cn. ^[4] College of Water Sciences, Beijing Normal University, Beijing 100875, China. ^[5]

关键词 Double mass curve Machine learning Sample entropy Water quality Yangtze River

DOI 10.1016/j.scitotenv.2021.147134

PMID 33940408

发布时间 2021-06-08

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