Prediction of reservoir evaporation considering water temperature and using ANFIS hybridized with metaheuristic algorithms
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Link
https://link.springer.com/content/pdf/10.1007/s12145-024-01223-8.pdf
Reference84 articles.
1. Abed M, Imteaz MA, Ahmed AN, Huang YF (2021) Application of long short-term memory neural network technique for predicting monthly pan Evaporation. Sci Rep 11:20742. https://doi.org/10.1038/s41598-021-99999-y
2. Adnan RM, Mostafa RR, Elbeltagi A, Yaseen ZM, Shahid S, Kisi O (2022a) Development of new machine learning model for streamflow prediction: case studies in Pakistan. Stoch Env Res Risk Assess 36:999–1033. https://doi.org/10.1007/s00477-021-02111-z(0123456789)
3. Adnan RM, Jaafari A, Milan SG, Kisi O, Heddam S, Zounemat-Kermani M (2022b) Hybridized Adaptive Neuro-Fuzzy Inference System with Metaheuristic Algorithms for Modeling Monthly Pan Evaporation. Water 14:3549. https://doi.org/10.3390/w14213549
4. Adnan RM, Petroselli A, Heddam S, Guimarães Santos CA, Kisi O (2021a) Comparison of different methodologies for rainfall-runoff modeling: machine learning vs conceptual approach. Nat Hazards 105:2987–3011. https://doi.org/10.1007/s11069-020-04438-2
5. Adnan RM, Petroselli A, Heddam S, Guimarães Santos CA, Kisi O (2021b) Short term rainfall-runoff modelingusing several machine learning methods and a conceptual event-based model. Stoch Env Res Risk A 35:597–616. https://doi.org/10.1007/s00477-020-01910-0
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