首页|Studies from Southeast University Reveal New Findings on Machine Learning (Nonli near Unsteady Aerodynamic Forces Prediction and Aeroelastic Analysis of Wind-ind uced Bridge Response At Multiple Wind Speeds: a Deep Learning-based Reduced-orde r ...)
Studies from Southeast University Reveal New Findings on Machine Learning (Nonli near Unsteady Aerodynamic Forces Prediction and Aeroelastic Analysis of Wind-ind uced Bridge Response At Multiple Wind Speeds: a Deep Learning-based Reduced-orde r ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Machine Learning are discussed in a new report.According to news originating from Nanjing, Peopl e’s Republic of China, by NewsRx correspondents, research stated, “Machine learn ing-based aerodynamic reduced-order models (ROMs) combine high accuracy with ext remely low computational costs, making them highly effective in predicting nonli near and unsteady bridge aerodynamic forces.Although several machine learning-b ased nonlinear aerodynamic models have been developed, the majority are built on a single wind speed parameter.”
NanjingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningSoutheast University
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