Data from Peking University Advance Knowledge in Computational Physics (Vpvnet: a Velocity-pressure-vorticity Neural Network Method for the Stokes’ Equations Under Reduced Regularity)

摘要

By a News Reporter-Staff News Editor at Network Daily News – Investigators publish new report on Physics - Computational Physics. According to news reporting out of Beijing, People’s Republic of China, by NewsRx editors, research stated, “We present VPVnet, a deep neural network method for the Stokes’ equations under reduced regularity. Different with recently proposed deep learning methods [40,51] which are based on the original form of PDEs, VPVnet uses the least square functional of the first-order velocity-pressure-vorticity (VPV) formulation ( [30]) as loss functions.”