Machine-learning-based water quality management of river with serial impoundments in the Republic of Korea

Machine-learning-based water quality management of river with serial impoundments in the Republic of Korea

Abstracts: Study region: Euiam Lake in the Republic of Korea Study focus: This study establishes a framework to prioritize total phosphorus (TP) management strategies based on machine learning (ML). A comparative analysis is conducted to evaluate the performance of four ML methods: random forest (R...

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Bibliographic Details
Main Authors: Hye Won Lee, Min Kim, Hee Won Son, Baehyun Min, Jung Hyun Choi
Format: Article
Language:English
Published: Elsevier 2022-06-01
Series:Journal of Hydrology: Regional Studies
Subjects:
Machine learning (ML)
Water quality
Serial impoundment
Long short-term memory (LSTM)
Gradient-based analysis
Online Access:http://www.sciencedirect.com/science/article/pii/S2214581822000829

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http://www.sciencedirect.com/science/article/pii/S2214581822000829

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