Machine Learning-Based Predominant Driving Factors Impacting Urban Industrial Wastewater Discharge in the Yellow River Basin-Reference-Cited by-同舟云学术

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Machine Learning-Based Predominant Driving Factors Impacting Urban Industrial Wastewater Discharge in the Yellow River Basin

Published:2023-01-06 Issue: Volume: Page:
ISSN:2690-0637
Container-title:ACS ES&T Water
language:en
Short-container-title:ACS EST Water

Author:

Xia Libo¹,Wu Beibei¹,Dai Anqi¹,Zhou Yun¹^ORCID

Affiliation:

1. College of Resources and Environment, Huazhong Agricultural University, Wuhan430070, China

Funder

Huazhong Agricultural University

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Water Science and Technology,Environmental Chemistry,Chemistry (miscellaneous),Chemical Engineering (miscellaneous)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsestwater.2c00596

Reference64 articles.

1. Evaluation of ecological city and analysis of obstacle factors under the background of high-quality development: Taking cities in the Yellow River Basin as examples

2. Insights into water sustainability from a grey water footprint perspective in an irrigated region of the Yellow River Basin

3. Grey water footprint evaluation and driving force analysis of eight economic regions in China

4. Arsenic pollution of sediments in China: An assessment by geochemical baseline

5. Source apportionment of potentially toxic elements in soils of the Yellow River Delta Nature Reserve, China: The application of three receptor models and geostatistical independent simulation

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning-based global trends and the development prospects of wastewater treatment: A bibliometric analysis;Journal of Environmental Chemical Engineering;2024-06

2. Applications of Artificial Intelligence, Machine Learning, and Data Analytics in Water Environments;ACS ES&T Water;2024-03-08

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