首页|Reports from Federal Institute of Education Science and Technology Provide New I nsights into Machine Learning (Estimating Energy Efficiency of the Aeration Proc ess of Stored Grains Through Machine Learning)
Reports from Federal Institute of Education Science and Technology Provide New I nsights into Machine Learning (Estimating Energy Efficiency of the Aeration Proc ess of Stored Grains Through Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. According to news reporting originating in Rio Verde, Brazil, by NewsRx journalists, research stated, “Aeration is carried out by blowing exte rnal air into the silo, with the aim to keep the temperature in the mass of stor ed grains at safe levels. In the present study, the energy efficiency of aeratio n of stored sunflower grains was estimated, and a model was proposed and tested to estimate the energy efficiency of aeration, using different algorithms in sup ervised and unsupervised machine learning.”
Rio VerdeBrazilSouth AmericaCyborg sEmerging TechnologiesMachine LearningFederal Institute of Education Scien ce and Technology
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