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Landslide susceptibility prediction using artificial neural networks, SVMs and random forest: hyperparameters tuning by genetic optimization algorithm

Crossref DOI link: https://doi.org/10.1007/s13762-022-04491-3

Published Online: 2022-09-21

Published Print: 2023-01

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

Authors

Daviran, M.

Shamekhi, M.

Ghezelbash, R.

Maghsoudi, A.
License Information

Text and Data Mining valid from 2022-09-21

Version of Record valid from 2022-09-21
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Article History

Received: 2 October 2021

Revised: 23 July 2022

Accepted: 18 August 2022

First Online: 21 September 2022

Declarations

:

: The authors have no conflict of interest.

: The codes that support the findings of this study are available at figshare.com with the private link [].

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