Hybrid COOT-ANN: a novel optimization algorithm for prediction of daily crop reference evapotranspiration in Australia
Author:
Publisher
Springer Science and Business Media LLC
Subject
Atmospheric Science
Link
https://link.springer.com/content/pdf/10.1007/s00704-023-04552-8.pdf
Reference59 articles.
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2. Achite M, Jehanzaib M, Sattari MT, Toubal AK, Elshaboury N, Wałęga A, Krakauer N, Yoo JY, Kim TW (2022) Modern techniques to modeling reference evapotranspiration in a semiarid area based on ANN and GEP models. Water 14:1210. https://doi.org/10.3390/w14081210
3. Adnan RM, Heddam S, Yaseen ZM, Shahid S, Kisi O, Li B (2021) Prediction of potential evapotranspiration using temperature-based heuristic approaches. Sustainability 13:297. https://doi.org/10.3390/su13010297
4. Ahmadi F, Mehdizadeh S, Mohammadi B, Pham QB, Doan TNC, Vo ND (2021) Application of an artificial intelligence technique enhanced with intelligent water drops for monthly reference evapotranspiration estimation. Agric Water Manag 244:106622. https://doi.org/10.1016/j.agwat.2020.106622
5. Ahmed AAM, Deo RC, Feng Q, Ghahramani A, Raj N, Yin Z, Yang L (2022) Hybrid deep learning method for a week-ahead evapotranspiration forecasting. Stoch Environ Res Risk Assess 36:831–849. https://doi.org/10.1007/s00477-021-02078-x
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