Runoff Forecasting of Machine Learning Model Based on Selective Ensemble
Author:
Publisher
Springer Science and Business Media LLC
Subject
Water Science and Technology,Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11269-023-03566-1.pdf
Reference39 articles.
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3. Alobaidi MH, Ouarda TBMJ, Marpu PR, Chebana F (2021) Diversity-driven ANN-based ensemble framework for seasonal low-flow analysis at ungauged sites. Adv Water Resour 147:103814. https://doi.org/10.1016/j.advwatres.2020.103814
4. Bashir D, Montañez GD, Sehra S, Segura PS, Lauw J, Gallagher M, Moustafa N, Lakshika E (2020) An information-theoretic perspective on overfitting and underfittinglecture notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Science and Business Media Deutschland GmbH, p 347–358. https://doi.org/10.1007/978-3-030-64984-5_27
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