Prediction of algal blooms via data-driven machine learning models: an evaluation using data from a well-monitored mesotrophic lake
<p>With increasing lake monitoring data, data-driven machine learning (ML) models might be able to capture the complex algal bloom dynamics that cannot be completely described in process-based (PB) models. We applied two ML models, the gradient boost regressor (GBR) and long short-term memory...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2023-01-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/16/35/2023/gmd-16-35-2023.pdf |