ListarDIR-Artículos, capítulos... por tema "Machine learning"
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AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models
(MDPI, 2022)Accurately forecasting reference evapotranspiration (ET0) values is crucial to improve crop irrigation scheduling, allowing anticipated planning decisions and optimized water resource management and agricultural production. ... -
Assessing Machine Learning Models for Gap Filling Daily Rainfall Series in a Semiarid Region of Spain
(MDPI, 2021)The presence of missing data in hydrometeorological datasets is a common problem, usually due to sensor malfunction, deficiencies in records storage and transmission, or other recovery procedures issues. These missing ...