首页|Research Conducted at Thammasat University Has Updated Our Knowledge about Machi ne Learning (Parametric Nonlinear Model Reduction Using Machine Learning On Gras smann Manifold With an Application On a Flow Simulation)
Research Conducted at Thammasat University Has Updated Our Knowledge about Machi ne Learning (Parametric Nonlinear Model Reduction Using Machine Learning On Gras smann Manifold With an Application On a Flow Simulation)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting originating from Pathum Thani , Thailand, by NewsRx correspondents, research stated, “Thiswork introduces a p arametric model order reduction (PMOR) approach that enhances an existing widelyused technique based on proper orthogonal decomposition (POD) and discrete empi rical interpolationmethod (DEIM) for parametrized nonlinear dynamical systems b y employing machine learning proceduresperformed on a Grassmann manifold. In pa rticular, distances between parameters are first computed basedon a metric defi ned on the Grassmann manifold of solution spaces.”
Pathum ThaniThailandAsiaCyborgsE merging TechnologiesMachine LearningThammasat University
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