Robust prediction of chlorophyll-A from nitrogen and phosphorus content in Philippine and global lakes using fine-tuned, explainable machine learning
Chlorophyll-a (Chl-a) content in waterbodies is a primary indicator of algal biomass and is used to detect impending harmful algal blooms. This paper presents a methodology using 8 popular machine learning (ML) models for estimating Chl-a concentration from nutrient content in lakes. Different from...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Environmental Challenges |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667010024002221 |
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