首页|New Machine Learning Findings from Ohio State University Described (Explainable Machine Learning for Predicting Stomatal Conductance Across Multiple Plant Funct ional Types)
New Machine Learning Findings from Ohio State University Described (Explainable Machine Learning for Predicting Stomatal Conductance Across Multiple Plant Funct ional Types)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news originating from Columbus, Ohio, by NewsRx correspo ndents, research stated, “Stomatal conductance (gs) is a key leaflevel function controlling water, carbon, and energy exchange between vegetation and the surro unding environment. Conventionally, semi-empirical models have been used to mode l gs, but these models require re-parameterization as ecosystems undergo phenolo gical changes over the growing season.” Funders for this research include National Science Foundation (NSF), National Ae ronautics & Space Administration (NASA), College of Food, Agricult ural and Environmental Sciences at Ohio State University.
ColumbusOhioUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningOhio State U niversity
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