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Comparative assessment of empirical and hybrid machine learning models for estimating daily reference evapotranspiration in sub-humid and semi-arid climates

Crossref DOI link: https://doi.org/10.1038/s41598-024-83859-6

Published Online: 2025-01-20

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Acharki, Siham https://orcid.org/0000-0001-9421-0807
Raza, Ali

Vishwakarma, Dinesh Kumar https://orcid.org/0000-0002-2421-6995
Amharref, Mina

Bernoussi, Abdes Samed

Singh, Sudhir Kumar

Al-Ansari, Nadhir https://orcid.org/0000-0002-6790-2653
Dewidar, Ahmed Z.

Al-Othman, Ahmed A.

Mattar, Mohamed A. https://orcid.org/0000-0002-7506-3036
Funding

Funding for this research was provided by:

Lulea University of Technology
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Text and Data Mining valid from 2025-01-20

Version of Record valid from 2025-01-20
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Article History

Received: 24 April 2024

Accepted: 18 December 2024

First Online: 20 January 2025

Declarations

:

: The authors declare no competing interests.

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