Predicting high-frequency nutrient dynamics in the Danube River with surrogate models using sensors and Random Forest

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Title:: Predicting high-frequency nutrient dynamics in the Danube River with surrogate models using sensors and Random Forest
Document type:: Zeitschriftenaufsatz
Author(s):: Tran, Yen Binh ; Arias-Rodriguez, Leonardo F. ; Huang, Jingshui
Keywords:: Water ; water quality ; surrogate ; nutrient concentration ; Random Forest ; Multiple Linear Regression ; soft sensor ; real-time
Journal title:: Frontiers in Water
Year:: 2022
Journal volume:: 4
Fulltext / DOI:: doi:10.3389/frwa.2022.894548
Publisher:: Frontiers Media S.A.
E-ISSN:: 2624-9375
Date of publication:: 17.08.2022
CC license:: by, https://creativecommons.org/licenses/by/4.0

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