Prediction of stream nitrogen and phosphorus concentrations from high-frequency sensors using Random Forests Regression-Reference-Cited by-同舟云学术

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Prediction of stream nitrogen and phosphorus concentrations from high-frequency sensors using Random Forests Regression

Published:2021-04 Issue: Volume:763 Page:143005
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Harrison Joel W.,Lucius Mark A.,Farrell Jeremy L.,Eichler Lawrence W.,Relyea Rick A.

Funder

Dormitory Authority of the State of New York

National Science Foundation

Publisher

Elsevier BV

Subject

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

Reference103 articles.

1. Past, present and prospect of an Artificial Intelligence (AI) based model for sediment transport prediction;Afan;J. Hydrol.,2016

2. Machine learning methods for better water quality prediction;Ahmed;J. Hydrol.,2019

3. Standard methods for the examination of water and wastewater;American Public Health Association,2017

4. A neural network experiment on the simulation of daily nitrate-nitrogen and suspended sediment fluxes from a small agricultural catchment;Anctil;Ecol. Model.,2009

5. A survey of cross-validation procedures for model selection;Arlot;Statistical Surveys,2010

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