Establishing Optimal Machine Learning Models for Monitoring Water Quality in Vietnam’s Upper Ma River

Establishing Optimal Machine Learning Models for Monitoring Water Quality in Vietnam’s Upper Ma River

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This study aims to establish the optimal regression model for predicting total suspended solids (TSS) and Turbidity based on in situ data and spectral regions of Sentinel-2 images. Various machine learning models were evaluated, including Multilayer Perceptron Regression (MLPR), Random Forest Regre...

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Bibliographic Details
Main Authors: Ngo Thanh Son, Nguyen Duc Loc
Format: Article
Language:English
Published: Environmental Research Institute, Chulalongkorn University 2024-11-01
Series:Applied Environmental Research
Subjects:
Water quality monitoring
Machine learning model
Sentinel-2 imagery
Turbidity
Total suspended solids
Upper Ma river
Online Access:https://ph01.tci-thaijo.org/index.php/aer/article/view/257524
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