摘要
Lacking labeled examples of working numerical strategies,adapting an iterative solver to accommodate a numerical issue,e.g.,density discontinuities in the pressure Poisson equation,is non-trivial and usually involves a lot of trial and error.Here,we resort to evolutionary neural network.A evolutionary neural network observes the outcome of an action and adapts its strategy accordingly.The process requires no labeled data but only a measure of a network’s performance at a task.Applying neuro-evolution and adapting the Jacobi iterative method for the pressure Poisson equation with density discontinuities,we show that the adapted Jacobi method is able to accommodate density discontinuities.
基金
Shi acknowledges financial support from the National Natural Science Foundation of China(Grant 91752202).
