Prediction of copper contamination in soil across EU using spectroscopy and machine learning: Handling class imbalance problem
Soil copper (Cu) pollution is a significant global environmental challenge, necessitating accurate assessment methods for effective control. However, existing classification approaches for Cu content in soil spectral datasets often face imbalances in data distribution, resulting in unreliable identi...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Smart Agricultural Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375524003320 |
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