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Using multivariate adaptive regression splines and extremely randomized trees algorithms to predict dust events frequency around an international wetland and prioritize its drivers

Crossref DOI link: https://doi.org/10.1007/s10661-021-09198-5

Published Online: 2021-06-22

Published Print: 2021-07

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

Authors

Ebrahimi-Khusfi, Zohre https://orcid.org/0000-0002-1036-6386
Nafarzadegan, Ali Reza https://orcid.org/0000-0002-1687-4787
Khosroshahi, Mohammad
License Information

Text and Data Mining valid from 2021-06-22

Version of Record valid from 2021-06-22
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Article History

Received: 11 March 2021

Accepted: 7 June 2021

First Online: 22 June 2021

Declarations

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: All authors provide informed written consent to the publication of the data contained in this article.

: The authors declare no competing interests.

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