Modeling Monthly Evaporation in Different Climates Using ANN–COOT Hybrid Algorithm
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s40996-023-01338-w.pdf
Reference18 articles.
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2. Ahmadi F, Mehdizadeh S, Mohammadi B, Pham QB, Doan TN, 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
3. Arya Azar N, Kardan N, Ghordoyee Milan S (2021) Developing the artificial neural network–evolutionary algorithms hybrid models (ANN–EA) to predict the daily evaporation from dam reservoirs. Eng Comput 39(2):1375–1393. https://doi.org/10.1007/s00366-021-01523-3
4. Ashrafzadeh A, Ghorbani MA, Biazar SM, Yaseen ZM (2019) Evaporation process modelling over northern Iran: application of an integrative data-intelligence model with the krill herd optimization algorithm. Hydrol Sci J 65(15):1843–1856. https://doi.org/10.1080/02626667.2019.1676428
5. Boden TA, Krassovski M, Yang B (2013) The AmeriFlux data activity and data system: an evolving collection of data management techniques, tools, products and services. Geosci Instrum Methods Data Syst 2:165–176. https://doi.org/10.5194/gi-2-165-2013
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