Prediction of evapotranspiration and soil moisture in different rice growth stages through improved salp swarm based feature optimization and ensembled machine learning algorithm-Reference-Cited by-同舟云学术

Prediction of evapotranspiration and soil moisture in different rice growth stages through improved salp swarm based feature optimization and ensembled machine learning algorithm

Published:2023-05-29 Issue:1-2 Volume:153 Page:649-673
ISSN:0177-798X
Container-title:Theoretical and Applied Climatology
language:en
Short-container-title:Theor Appl Climatol

Author:

Majumdar Parijata,Bhattacharya Diptendu,Mitra Sanjoy

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Link

https://link.springer.com/content/pdf/10.1007/s00704-023-04414-3.pdf

Reference52 articles.

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2. Ahmadianfar I, Heidari AA, Gandomi AH et al (2021) Run beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method. Expert Syst Appl 181:115079. https://doi.org/10.1016/j.eswa.2021.115079

3. Ahmadianfar I, Heidari AA, Noshadian S et al (2022) Info: An efficient optimization algorithm based on weighted mean of vectors. Expert Syst Appl 195:116516. https://doi.org/10.1016/j.eswa.2022.116516

4. Allen RG, Pereira LS, Raes D et al (1998) Crop evapotranspiration-guidelines for computing crop water requirements-FAO irrigation and drainage paper 56. FAO, Rome 300(9):D05109

5. Banik R, Das P, Ray S et al (2021) Prediction of electrical energy consumption based on machine learning technique. Electr Eng 103(2):909–920. https://doi.org/10.1007/s00202-020-01126-z

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