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Abstract Physics informed neural network (PINN) demonstrates powerful capabilities in solving forward and inverse problems of nonlinear partial 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. https://www.sukrensi.com/flash-sale-Ribavirin-500MG-R0077-500MG-p9633-big-savings/

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