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Ensemble machine learning paradigms in hydrology: A review

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Zounemat-Kermani, Mohammad, Batelaan, Okke, Fadaee, Marzieh, Hinkelmann, Reinhard·2021·Journal of Hydrology
DOI 10.1016/j.jhydrol.2021.126266
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Research works printed but not linked: 34

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Metadata

Authors
Zounemat-Kermani, M., Batelaan, O., Fadaee, M., & Hinkelmann, R.
Venue
Journal of Hydrology
Publisher
Elsevier BV
Published
2021-07
Volume
598
Pages
126266
ISSN
0022-1694 (ISSN-L)
DOI
10.1016/j.jhydrol.2021.126266
OpenAlex
W3151640016
Cited by
649
References
124
FWCI
31.29
Type
journal article
Language
en
Open access
green
Licence
Funders
Alexander von Humboldt-Stiftung

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Zounemat-Kermani, M., Batelaan, O., Fadaee, M., & Hinkelmann, R. (2021). Ensemble machine learning paradigms in hydrology: A review. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2021.126266

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.