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Machine Learning Analysis of Coastal Water Pollution in China: Drivers and Complex Relationships Cover

Machine Learning Analysis of Coastal Water Pollution in China: Drivers and Complex Relationships

Ecological Chemistry and Engineering S
Volume 33 (2026): Issue 1 (March 2026)
By: Dehong Sun,  Senwei Zheng and  Yinhui Yu  
Open Access
|Apr 2026
Authors

Authors

Dehong Sun

155065349@163.com

Minnan University of Science and Technology, Quanzhou, China

Senwei Zheng

84246354@qq.com

Minnan University of Science and Technology, Quanzhou, China

Yinhui Yu

Minnan University of Science and Technology, Quanzhou, China
DOI: https://doi.org/10.2478/eces-2026-0003 | Journal eISSN: 2084-4549 | Journal ISSN: 1898-6196
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Language: English
Page range: 47 - 62
Published on: Apr 18, 2026
Published by: Society of Ecological Chemistry and Engineering
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
seawater pollution,
sustainable development,
machine learning,
generalised additive model (GAM),
nonlinear effects
Related subjects:
Chemistry,
Sustainable and green chemistry,
Engineering,
Electrical engineering,
Energy engineering,
Life sciences,
Ecology

© 2026 Dehong Sun, Senwei Zheng, Yinhui Yu, published by Society of Ecological Chemistry and Engineering
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 33 (2026): Issue 1 (March 2026)
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