首页|Studies from National Center for Scientific Research (CNRS) Yield New Data on Machine Learning (An Unsupervised Machine Learn- ing Approach To Reduce Nonlinear Fe2 Multiscale Calculations Us- ing Macro Clustering)
Studies from National Center for Scientific Research (CNRS) Yield New Data on Machine Learning (An Unsupervised Machine Learn- ing Approach To Reduce Nonlinear Fe2 Multiscale Calculations Us- ing Macro Clustering)
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NETL
NSTL
Elsevier
2024 FEB 02 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting originating in Marne la Vallee, France, by NewsRx journalists, research stated, “Solving nonlinear multiscale methods with history-dependent behaviors and fine macroscopic meshes is a well-known chal- lenge. In this work, an unsupervised machine learning-based clustering approach is developed to reduce nonlinear Multilevel Finite Element-FE2 calculations.” Financial support for this research came from Bosch Research Foundation.
Marne la ValleeFranceEuropeCyborgsEmerging Technolo- giesMachine LearningNational Center for Scientific Research (CNRS)
NETL
NSTL
Elsevier
