首页|Researchers from University of Arizona Describe Findings in Machine Learning (Ph ysics-informed Hybrid Modeling Methodology for Building Infiltration)
Researchers from University of Arizona Describe Findings in Machine Learning (Ph ysics-informed Hybrid Modeling Methodology for Building Infiltration)
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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 from Tucson, Arizona, by Ne wsRx journalists, research stated, "Infiltration is responsible for one-third to one-half of the space conditioning load of a typical residential home, but the modeling of infiltration for building energy modeling is either represented by o ver-simplified equations or dependent on over-generalized rules of thumb. This p aper develops a physics-informed data-driven methodology for modeling infiltrati on using building-specific empirical measurements." Financial supporters for this research include United States Department of Energ y (DOE), United States Department of Energy (DOE).
TucsonArizonaUnited StatesNorth an d Central AmericaCyborgsEmerging TechnologiesMachine LearningUniversity of Arizona
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