Integration of extreme learning machines with CEEMDAN and VMD techniques in the prediction of the multiscalar standardized runoff index and standardized precipitation evapotranspiration index-Reference-Cited by-同舟云学术

Integration of extreme learning machines with CEEMDAN and VMD techniques in the prediction of the multiscalar standardized runoff index and standardized precipitation evapotranspiration index

Published:2023-10-15 Issue:1 Volume:120 Page:825-849
ISSN:0921-030X
Container-title:Natural Hazards
language:en
Short-container-title:Nat Hazards

Author:

Katipoğlu Okan Mert^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology

Link

https://link.springer.com/content/pdf/10.1007/s11069-023-06238-w.pdf

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4. Almikaeel W, Čubanová L, Šoltész A (2022) Hydrological drought forecasting using machine learning—Gidra river case study. Water 14:387. https://doi.org/10.3390/w14030387

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