Optimization of supervised learning models for modeling of mean monthly flows
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-022-07406-y.pdf
Reference49 articles.
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3. Ibrahim KSMH, Huang YF, Ahmed AN, Koo CH, El-Shafie A (2022) A review of the hybrid artificial intelligence and optimization modelling of hydrological streamflow forecasting. Alex Eng J 61:279–303. https://doi.org/10.1016/j.aej.2021.04.100
4. Yadav B, Mathur S (2020) River discharge simulation using variable parameter McCarthy–Muskingum and wavelet-support vector machine methods. Neural Comput Appl 32:2457–2470. https://doi.org/10.1007/s00521-018-3745-1
5. Young CC, Liu WC, Chung CE (2015) Genetic algorithm and fuzzy neural networks combined with the hydrological modeling system for forecasting watershed runoff discharge. Neural Comput Appl 26:1631–1643. https://doi.org/10.1007/s00521-015-1832-0
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