AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models
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Bellido-Jiménez, J.A.; Estévez, J.; Vanschoren, J.; García-Marín, A.P. AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models. Agronomy 2022, 12, 656. https://doi.org/10.3390/agronomy12030656
Bellido-Jiménez JA, Estévez J, Vanschoren J, García-Marín AP. AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models. Agronomy. 2022; 12(3):656. https://doi.org/10.3390/agronomy12030656
Chicago/Turabian StyleBellido-Jiménez, Juan A., Javier Estévez, Joaquin Vanschoren, and Amanda P. García-Marín. 2022. "AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models" Agronomy 12, no. 3: 656. https://doi.org/10.3390/agronomy12030656