A comparison of various machine learning approaches performance for prediction suspended sediment load of river systems: A case study in Malaysia
Accurate and reliable suspended sediment load (SSL) prediction models are necessary for the planning and management of water resource structures. In this study, four machine learning techniques, namely Gradient boost regression (GBT), Random Forest (RF), Support vector machine (SVM), and Artificial...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Published: |
Springer Heidelberg
2022
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/33746/ |
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