首页|New Machine Learning Findings from University of Washington Described (Efficient Analysis of Composites Manufacturing Using Multi-fidelity Simulation and Probab ilistic Machine Learning)
New Machine Learning Findings from University of Washington Described (Efficient Analysis of Composites Manufacturing Using Multi-fidelity Simulation and Probab ilistic Machine Learning)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
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 originating in Seattle, Washi ngton, by NewsRx journalists, research stated, “This paper introduces an innovat ive approach for the efficient analysis of composites manufacturing processes an d phenomena. The method combines low- and high-fidelity simulation schemes with limited amounts of experimental data to train surrogate machine learning (ML) mo dels.” Financial support for this research came from Toray Composite Materials America, Inc. - Italian Minister of Foreign Affairs and INTERNATIONAL COOPERATION (MAECI ).
SeattleWashingtonUnited StatesNort h and Central AmericaCyborgsEmerging TechnologiesMachine LearningUnivers ity of Washington
NETL
NSTL
