Articles | Volume 24, issue 5
https://doi.org/10.5194/nhess-24-1657-2024
© Author(s) 2024. This work is distributed under the Creative Commons Attribution 4.0 License.
Research article
| 
14 May 2024
Research article |
| 14 May 2024
| 14 May 2024
Application of the teaching–learning-based optimization algorithm to an analytical model of thunderstorm outflows to analyze the variability of the downburst kinematic and geometric parameters
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Abd-Elaal, E. S., Mills, J. E., and Ma, X.: A coupled parametric-CFD study for determining ages of downbursts through investigation of different field parameters, J. Wind Eng. Ind. Aerod., 123, 30–42, 2013.
Abdi, H. and Williams, L. J.: Principal component analysis, Wiley Interdisciplinary Reviews: Computational Statistics, 2, 433–459, 2010.
Amato, F., Guignard, F., Robert, S., and Kanevski, M.: A novel framework for spatio-temporal prediction of environmental data using deep learning, Sci. Rep.-UK, 10, 22243, https://doi.org/10.1038/s41598-020-79148-7, 2020.
Bjerknes, J. and Solberg, H.: Life cycle of cyclones and polar front theory of atmospheric circulation, Geophysiks Publikationer, 3, 3–18, 1922.
Bogensperger, A. and Fabel, Y.: A practical approach to cluster validation in the energy sector, Energy Inform, 4, 18, https://doi.org/10.1186/s42162-021-00177-1, 2021.
