Comparative assessment of advanced machine learning techniques for simulation of lake water level fluctuations based on different dimensionality reduction methods-Reference-Cited by-同舟云学术

Comparative assessment of advanced machine learning techniques for simulation of lake water level fluctuations based on different dimensionality reduction methods

Published:2023-01-28 Issue:1 Volume:16 Page:37-55
ISSN:1865-0473
Container-title:Earth Science Informatics
language:en
Short-container-title:Earth Sci Inform

Author:

Riazi Mostafa,Karimi Maryam,Eslamian Saeid,Riahi Samani Majid

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

https://link.springer.com/content/pdf/10.1007/s12145-023-00951-7.pdf

Reference96 articles.

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3. AghaKouchak A et al (2015) Aral Sea syndrome desiccates Lake Urmia: call for action. J Great Lakes Res 41:307–311. https://doi.org/10.1016/j.jglr.2014.12.007

4. Ahmady-Birgani H et al (2020) On the chemical nature of wet deposition over a major desiccated lake: case study for Lake Urmia basin. Atmos Res 234:104762. https://doi.org/10.1016/j.atmosres.2019.104762

5. Alizamir M et al (2020) A novel method for lake level prediction: deep echo state network. Arab J Geosci 13:1–18. https://doi.org/10.1007/s12517-020-05965-9

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