首页|Findings on Machine Learning Reported by Investigators at Universityof Tennesse e (Afsd-nets: a Physics-informed Machine Learning Model for Predicting the Tempe rature Evolution During Additive Friction Stir Deposition)
Findings on Machine Learning Reported by Investigators at Universityof Tennesse e (Afsd-nets: a Physics-informed Machine Learning Model for Predicting the Tempe rature Evolution During Additive Friction Stir Deposition)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news reportingfrom Knoxville, Tennessee, by News Rx journalists, research stated, “This study models the temperatureevolution du ring additive friction stir deposition (AFSD) using machine learning. AFSD is a solid-stateadditive manufacturing technology that deposits metal using plastic flow without melting.”
KnoxvilleTennesseeUnited StatesNor th and Central AmericaCyborgsEmerging TechnologiesMachine LearningUniver sity of Tennessee
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