首页|Findings from Florida State University Broaden Understanding of Machine Learning (Choice of Interior Penalty Coefficient for Interior Penalty Discontinuous Gale rkin Method for Biot’s System By Employing Machine Learning)
Findings from Florida State University Broaden Understanding of Machine Learning (Choice of Interior Penalty Coefficient for Interior Penalty Discontinuous Gale rkin Method for Biot’s System By Employing Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting from Tallahassee, Florida, by NewsRx journalists, research stated, “This paper uses neural networks and machine lear ning to study the optimal choice of the interior penalty parameter of the discon tinuous Galerkin finite element methods for both the elliptic problems and Biot ’ s systems. It is crucial to choose the optimal interior penalty parameter, which is not too small or too large for the stability, robustness, and efficiency of the approximated numerical solutions.”
TallahasseeFloridaUnited StatesNor th and Central AmericaCyborgsEmerging TechnologiesMachine LearningFlorid a State University
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