Predictive modeling of nitrogen and phosphorus concentrations in rivers using a machine learning framework: A case study in an urban-rural transitional area in Wenzhou China-Reference-Cited by-同舟云学术

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Predictive modeling of nitrogen and phosphorus concentrations in rivers using a machine learning framework: A case study in an urban-rural transitional area in Wenzhou China

Published:2024-02 Issue: Volume:910 Page:168521
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Xue Jingyuan,Yuan Can,Ji Xiaoliang,Zhang Minghua

Funder

China Agricultural University

Sichuan University

Fundamental Research Funds for the Central Universities

Wenzhou Medical University

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference66 articles.

1. Improving bug fix-time prediction model by filtering out outliers;AbdelMoez,2013

2. Relevant factors in the eutrophication of the Uruguay River and the Río Negro;Beretta-Blanco;Sci. Total Environ.,2021

3. A comparison of results from a hydrologic transport model (HSPF) with distributions of sulfate and mercury in a mine-impacted watershed in northeastern Minnesota;Berndt;J. Environ. Manag.,2016

4. Characterization of phosphorus interaction with sediments affected by acid mine drainage-relation with the sediment composition;Boukemara;Int. J. Sed. Res.,2017

5. Classification and Regression Trees;Breiman,1984

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