Machine Learning Approaches for Predicting Health Risk of Cyanobacterial Blooms in Northern European Lakes

Machine Learning Approaches for Predicting Health Risk of Cyanobacterial Blooms in Northern European Lakes

Cyanobacterial blooms are considered a major threat to global water security with documented impacts on lake ecosystems and public health. Given that cyanobacteria possess highly adaptive traits that favor them to prevail under different and often complicated stressor regimes, predicting their abund...

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Bibliographic Details
Main Authors: Nikolaos Mellios, S. Jannicke Moe, Chrysi Laspidou
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Water
Subjects:
cyanobacteria blooms
eutrophication
lakes monitoring data
path analysis
machine learning algorithms
Decision Tree
Online Access:https://www.mdpi.com/2073-4441/12/4/1191

Internet

https://www.mdpi.com/2073-4441/12/4/1191

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