Predicting and analyzing the algal population dynamics of a grass-type lake with explainable machine learning

Algal blooms, exacerbated by climate change and eutrophication, have emerged as a global concern. In this study, we introduce a novel interpretable machine learning (ML) workflow tailored for investigating the dynamics of algal populations in grass-type lakes, Liangzi lake. Utilizing seven ML method...

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Veröffentlicht in:Journal of environmental management 2024-03, Vol.354, p.120394-120394, Article 120394
Hauptverfasser: Cui, Hao, Tao, Yiwen, Li, Jian, Zhang, Jinhui, Xiao, Hui, Milne, Russell
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Sprache:eng
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