Interpreting machine learning models based on SHAP values in predicting suspended sediment concentration
Machine learning (ML) has become a powerful tool for predicting suspended sediment concentration (SSC). Nonetheless, the ability to interpret the physical process is considered the main issue in applying most of ML approaches. In this regard, the current study presents a novel framework involving fo...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-02-01
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| Series: | International Journal of Sediment Research |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1001627924001070 |
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