POSSIBILITY OF ENERGY RECOVERY FROM AIRFLOW AROUND AN SUV-CLASS CAR BASED ON WIND TUNNEL TESTING


Data-driven solutions and parameter estimations of a family of higher-order KdV equations based on physics informed neural networks

Abstract Physics informed neural network (PINN) demonstrates powerful capabilities in solving forward and inverse problems of nonlinear partial Cheese Knife differential equations (NLPDEs) through combining data-driven and physical constraints.In this paper, two PINN methods that adopt tanh and sine as activation functions, respectively, are used t

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