Application of hybrid machine learning-based ensemble techniques for rainfall-runoff modeling
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Link
https://link.springer.com/content/pdf/10.1007/s12145-023-01041-4.pdf
Reference66 articles.
1. Abba SI, Linh NTT, Abdullahi J, Ali SIA, Pham QB, Abdulkadir RA, Costache R, Nam VT, Anh DT (2020) Hybrid machine learning ensemble techniques for modeling dissolved oxygen concentration. IEEE Access 8:157218–157237. https://doi.org/10.1109/ACCESS.2020.3017743
2. Abedi R, Costache R, Shafizadeh-Moghadam H, Pham QB (2022) Flash-flood susceptibility mapping based on XGBoost, random forest and boosted regression trees. Geocarto Int 37(19):5479–5496. https://doi.org/10.1080/10106049.2021.1920636
3. Abinayadhevi, P, Prasad, SJS (2015) Identification of pH process using Hammerstein-Wiener model. Proceedings of 2015 IEEE 9th International Conference on Intelligent Systems and Control, ISCO 2015, 1–5. https://doi.org/10.1109/ISCO.2015.7282297
4. Adnan RM, Liang Z, Trajkovic S, Zounemat-Kermani M, Li B, Kisi O (2019) Daily streamflow prediction using optimally pruned extreme learning machine. J Hydrol 577(July):123981. https://doi.org/10.1016/j.jhydrol.2019.123981
5. Adnan RM, Petroselli A, Heddam S, Santos CAG, Kisi O (2021) Short term rainfall-runoff modelling using several machine learning methods and a conceptual event-based model. Stoch Env Res Risk A 35(3):597–616. https://doi.org/10.1007/s00477-020-01910-0
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