Coupling machine learning with signal process techniques and particle swarm optimization for forecasting flood routing calculations in the Eastern Black Sea Basin, Türkiye-Reference-Cited by-同舟云学术

Coupling machine learning with signal process techniques and particle swarm optimization for forecasting flood routing calculations in the Eastern Black Sea Basin, Türkiye

Published:2023-01-30 Issue:16 Volume:30 Page:46074-46091
ISSN:1614-7499
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Katipoğlu Okan Mert^ORCID,Sarıgöl Metin^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s11356-023-25496-6.pdf

Reference64 articles.

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2. Akbari R, Hessami-Kermani MR, Shojaee S (2020) Flood routing: improving outflow using a new nonlinear muskingum model with four variable parameters coupled with PSO-GA algorithm. Water Resour Manage 34(10):3291–3316. https://doi.org/10.1007/s11269-020-02613-5

3. Alizadeh F, Faregh Gharamaleki A, Jalilzadeh R (2021) A two-stage multiple-point conceptual model to predict river stage-discharge process using machine learning approaches. J Water Clim Change 12(1):278–295. https://doi.org/10.2166/wcc.2020.006

4. Bagatur T, Onen F (2018) Development of predictive model for flood routing using genetic expression programming. J Flood Risk Manag 11:S444–S454. https://doi.org/10.1111/jfr3.12232

5. Ball JE (2022) Modelling accuracy for urban design flood estimation. Urban Water J 19(1):87–96. https://doi.org/10.1080/1573062X.2021.1955283

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