首页|Reports from Chinese Academy of Sciences Provide New Insights into Machine Learn ing (A Machine Learning Approach for Predicting the Johnson-champoux-allard Para meters of a Fibrous Porous Material)
Reports from Chinese Academy of Sciences Provide New Insights into Machine Learn ing (A Machine Learning Approach for Predicting the Johnson-champoux-allard Para meters of a Fibrous Porous Material)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting from Beijing, People’s Republ ic of China, by NewsRx journalists, research stated, “Porous fibrous materials h ave been widely used as acoustic treatments for noise attenuation. Their acousti c properties are typically characterized by Johnson-Champoux-Allard (JCA) model, which includes five dominant parameters, i.e., open porosity, flow resistivity, tortuosity, viscous characteristic length, and thermal characteristic length.”
BeijingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningChinese Academy of Sciences
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