首页|New Findings from Federal University in Machine Learning Provides New Insights ( Improving Actual Evapotranspiration Estimates Through an Integrated Remote Sensi ng and Cutting-edge Machine Learning Approach)
New Findings from Federal University in Machine Learning Provides New Insights ( Improving Actual Evapotranspiration Estimates Through an Integrated Remote Sensi ng and Cutting-edge Machine Learning Approach)
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2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Machine Learn ing have been published. According to news reporting originating in Vicosa, Braz il, by NewsRx journalists, research stated, "Recent technological advances have allowed the production of many studies on evapotranspiration, resulting in impro vements in reference evapotranspiration estimates and crop coefficients with rem ote sensing data. However, these two areas of research often work independently, producing valuable studies, but without an effective integration to predict act ual evapotranspiration directly, without the need for weather stations." Funders for this research include Coordenacao de Aperfeicoamento de Pessoal de N ivel Superior (CAPES), Conselho Nacional de Desenvolvimento Cientifico e Tecnolo gico (CNPQ), Federal University of Vicosa-UFV.
VicosaBrazilSouth AmericaCyborgsEmerging TechnologiesMachine LearningRemote SensingFederal University
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